Coursework - 2021
library("janitor")##
## Attaching package: 'janitor'## The following objects are masked from 'package:stats':
##
## chisq.test, fisher.testlibrary("here")## here() starts at C:/Users/mario/Desktop/Coursework2021library("tidyverse")## -- Attaching packages --------------------------------------- tidyverse 1.3.1 --## v ggplot2 3.3.5 v purrr 0.3.4
## v tibble 3.1.4 v dplyr 1.0.7
## v tidyr 1.1.4 v stringr 1.4.0
## v readr 2.0.2 v forcats 0.5.1## -- Conflicts ------------------------------------------ tidyverse_conflicts() --
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()library("lubridate")##
## Attaching package: 'lubridate'## The following objects are masked from 'package:base':
##
## date, intersect, setdiff, unionlibrary("ggrepel")
library("gapminder")
library("RColorBrewer")
library("readxl")#Question 1a
read_lines(file = here("data","nasa_global_temperature.txt"), n_max = 8L ) #read the first 8 lines of txt## [1] "Land-Ocean Temperature Index (C)" "--------------------------------"
## [3] "" "Year No_Smoothing Lowess(5)"
## [5] "----------------------------" "1880 -0.16 -0.09"
## [7] "1881 -0.08 -0.12" "1882 -0.10 -0.16"df <- read_table(here("data","nasa_global_temperature.txt"), skip = 3,) #import data and skip the first 3 lines##
## -- Column specification --------------------------------------------------------
## cols(
## Year = col_character(),
## No_Smoothing = col_double(),
## `Lowess(5)` = col_double()
## )## Warning: 1 parsing failure.
## row col expected actual file
## 1 -- 3 columns 1 columns 'C:/Users/mario/Desktop/Coursework2021/data/nasa_global_temperature.txt'dfnasa_temp <- df%>% #save the name of the tibble
select(c("Year", "No_Smoothing")) %>% #select the two columns
rename(date = Year) %>% #rename year as date
rename(temp = No_Smoothing)%>% #rename No_smoothing as temp
mutate(date = parse_date(date, format = "%Y")) %>% #create a new column, turn "date" into date and shows only the year
remove_empty() #remove columns and rows that has NAs ## value for "which" not specified, defaulting to c("rows", "cols")## Warning: 1 parsing failure.
## row col expected actual
## 1 -- date like %Y ----------------------------ggplot() + #create a plot
layer (
data = nasa_temp, #use the data from nasa_temp
geom = "line", #the type of plot is line graph
mapping = aes(x = date, y = temp), #specifies the data that we use in each axes
stat = "identity", #no further transformation
position = "identity" #position adjustment
)
#Question 1b
read_lines(file = here("data","nasa_arctic_sea_ice.csv"), n_max = 5L ) #read the first 5 lines of csv## [1] "year; mo; data-type; region; extent; area"
## [2] "1979; 9; Goddard; N; 7,05; 4,58"
## [3] "1980; 9; Goddard; N; 7,67; 4,87"
## [4] "1981; 9; Goddard; N; 7,14; 4,44"
## [5] "1982; 9; Goddard; N; 7,30; 4,43"df1 <- read_csv2(here("data","nasa_arctic_sea_ice.csv")) #import the data ## i Using "','" as decimal and "'.'" as grouping mark. Use `read_delim()` for more control.## Rows: 42 Columns: 6## -- Column specification --------------------------------------------------------
## Delimiter: ";"
## chr (2): data-type, region
## dbl (4): year, mo, extent, area##
## i Use `spec()` to retrieve the full column specification for this data.
## i Specify the column types or set `show_col_types = FALSE` to quiet this message.df1nasa_ice <- df1 %>% #save the name of the tibble
select(c(year, extent)) %>% #select the two columns
rename(date = year) %>% #rename year as date
rename(ice = extent) %>% #rename the extent as ice
mutate(date = as.character(date)) %>% #create a new column, turn "date" into character
mutate(date = parse_date(date, format = "%Y")) %>% #turn "date" into date
remove_empty() #remove columns and rows that has NAs ## value for "which" not specified, defaulting to c("rows", "cols")ggplot() + #create a plot
layer (
data = nasa_ice, #use the data from nasa_ice
geom = "line", #the type of plot is line graph
mapping = aes(x = date, y = ice), #specifies the data that we use in each axes
stat = "identity", #no further transformation
position = "identity" #position adjustment
)
#Question 1c
read_lines(file = here("data","nasa_sea_level.csv"), n_max = 15) #read the first 15 lines of csv## [1] "HDR Global Mean Sea Level Data"
## [2] "HDR"
## [3] "HDR This file contains Global Mean Sea Level (GMSL) variations computed at the NASA Goddard Space Flight Center under the "
## [4] "HDR auspices of the NASA Sea Level Change program. The GMSL was generated using the Integrated Multi-Mission Ocean Altimeter Data for "
## [5] "HDR Climate Research (http://podaac.jpl.nasa.gov/dataset/MERGED_TP_J1_OSTM_OST_ALL_V5). It combines Sea Surface Heights from "
## [6] "HDR TOPEX/Poseidon, Jason-1, OSTM/Jason-2, and Jason-3 to a common terrestrial reference frame with all inter-mission biases, range and "
## [7] "HDR geophysical corrections applied and placed onto a georeferenced orbit. This creates a consistent data record throughout "
## [8] "HDR time, regardless of the instrument used."
## [9] "HDR"
## [10] "HDR The data can be found below. A separate figure file, Global_Sea_Level_Graph, was generated using the GMSL data (listed in "
## [11] "HDR column 12 below) with the 60-day Gaussian type filter and having the Global Isostatic Adjustment (GIA) applied, with annual "
## [12] "HDR and semi-annual signals removed."
## [13] "HDR"
## [14] "HDR If you use these data please cite:"
## [15] "HDR GSFC. 2020. Global Mean Sea Level Trend from Integrated Multi-Mission Ocean Altimeters TOPEX/Poseidon, Jason-1, OSTM/Jason-2, and Jason-3 Version 5.0 Ver. 5.0 PO.DAAC, CA, USA. Dataset accessed [YYYY-MM-DD] at http://dx.doi.org/10.5067/GMSLM-TJ150."df2 <- read_table(here("data","nasa_sea_level.csv"), skip = 48,col_names = FALSE) #import the data with new column names and skip the first 48 lines##
## -- Column specification --------------------------------------------------------
## cols(
## X1 = col_double(),
## X2 = col_double(),
## X3 = col_double(),
## X4 = col_double(),
## X5 = col_double(),
## X6 = col_double(),
## X7 = col_double(),
## X8 = col_double(),
## X9 = col_double(),
## X10 = col_double(),
## X11 = col_double(),
## X12 = col_double()
## )df2glimpse(df2) #rotate the table## Rows: 1,048
## Columns: 12
## $ X1 <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 999, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 999,~
## $ X2 <dbl> 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27~
## $ X3 <dbl> 1993.012, 1993.039, 1993.066, 1993.093, 1993.120, 1993.147, 1993.1~
## $ X4 <dbl> 452600, 447591, 459462, 410064, 446813, 405085, 455531, 453661, 44~
## $ X5 <dbl> 327401.3, 324498.4, 333018.2, 297483.2, 321635.8, 291945.9, 327830~
## $ X6 <dbl> -38.59, -41.97, -41.93, -42.67, -37.86, -36.09, -36.11, -35.52, -3~
## $ X7 <dbl> 89.86, 90.86, 87.27, 90.75, 90.26, 89.99, 88.74, 89.49, 88.79, 98.~
## $ X8 <dbl> -38.76, -39.78, -39.62, -39.67, -38.75, -37.71, -36.85, -36.32, -3~
## $ X9 <dbl> -38.59, -41.97, -41.91, -42.65, -37.83, -36.05, -36.06, -35.47, -3~
## $ X10 <dbl> 89.86, 90.86, 87.27, 90.74, 90.25, 89.99, 88.74, 89.49, 88.78, 98.~
## $ X11 <dbl> -38.75, -39.77, -39.61, -39.64, -38.72, -37.67, -36.81, -36.27, -3~
## $ X12 <dbl> -38.57, -39.11, -38.58, -38.34, -37.21, -35.98, -34.94, -34.19, -3~nasa_sea <- df2 %>% #save the name of the tibble
rename(date = X3) %>% #rename X13 as date
rename(sea = X12) %>% #rename X12 as sea
select(c(date,sea)) %>% #select columns sea and date
mutate(date = date_decimal(date, tz = "UTC")) %>% #create a column and convert a decimal to date
mutate(date = date(date)) #turn date as date
ggplot() + #create a plot
layer (
data = nasa_sea, #use the data from nasa_sea
geom = "line", #the type of plot is line graph
mapping = aes(x = date, y = sea), #specifies the data that we use in each axes
stat = "identity", #no further transformation
position = "identity" #position adjustment
)
#Question 1d
read_lines(file = here("data","nasa_carbon_dioxide.txt"), n_max = 200L ) #read the first 15 lines of csv## [1] "# --------------------------------------------------------------------"
## [2] "# USE OF NOAA GML DATA"
## [3] "# "
## [4] "# These data are made freely available to the public and the"
## [5] "# scientific community in the belief that their wide dissemination"
## [6] "# will lead to greater understanding and new scientific insights."
## [7] "# The availability of these data does not constitute publication"
## [8] "# of the data. NOAA relies on the ethics and integrity of the user to"
## [9] "# ensure that GML receives fair credit for their work. If the data "
## [10] "# are obtained for potential use in a publication or presentation, "
## [11] "# GML should be informed at the outset of the nature of this work. "
## [12] "# If the GML data are essential to the work, or if an important "
## [13] "# result or conclusion depends on the GML data, co-authorship"
## [14] "# may be appropriate. This should be discussed at an early stage in"
## [15] "# the work. Manuscripts using the GML data should be sent to GML"
## [16] "# for review before they are submitted for publication so we can"
## [17] "# ensure that the quality and limitations of the data are accurately"
## [18] "# represented."
## [19] "# "
## [20] "# Contact: Pieter Tans (303 497 6678; pieter.tans@noaa.gov)"
## [21] "# "
## [22] "# File Creation: Tue Sep 7 11:58:43 2021"
## [23] "# "
## [24] "# RECIPROCITY"
## [25] "# "
## [26] "# Use of these data implies an agreement to reciprocate."
## [27] "# Laboratories making similar measurements agree to make their"
## [28] "# own data available to the general public and to the scientific"
## [29] "# community in an equally complete and easily accessible form."
## [30] "# Modelers are encouraged to make available to the community,"
## [31] "# upon request, their own tools used in the interpretation"
## [32] "# of the GML data, namely well documented model code, transport"
## [33] "# fields, and additional information necessary for other"
## [34] "# scientists to repeat the work and to run modified versions."
## [35] "# Model availability includes collaborative support for new"
## [36] "# users of the models."
## [37] "# --------------------------------------------------------------------"
## [38] "# "
## [39] "# "
## [40] "# See www.esrl.noaa.gov/gmd/ccgg/trends/ for additional details."
## [41] "# "
## [42] "# Data from March 1958 through April 1974 have been obtained by C. David Keeling"
## [43] "# of the Scripps Institution of Oceanography (SIO) and were obtained from the"
## [44] "# Scripps website (scrippsco2.ucsd.edu)."
## [45] "# Monthly mean CO2 constructed from daily mean values"
## [46] "# Scripps data downloaded from http://scrippsco2.ucsd.edu/data/atmospheric_co2"
## [47] "# Monthly values are corrected to center of month based on average seasonal"
## [48] "# cycle. Missing days can be asymmetric which would produce a high or low bias."
## [49] "# Missing months have been interpolated, for NOAA data indicated by negative stdev"
## [50] "# and uncertainty. We have no information for SIO data about Ndays, stdv, unc"
## [51] "# so that they are also indicated by negative numbers"
## [52] "# decimal monthly de-season #days st.dev unc. of"
## [53] "# date average alized of days mon mean"
## [54] " 1958 3 1958.2027 315.70 314.43 -1 -9.99 -0.99"
## [55] " 1958 4 1958.2877 317.45 315.16 -1 -9.99 -0.99"
## [56] " 1958 5 1958.3699 317.51 314.71 -1 -9.99 -0.99"
## [57] " 1958 6 1958.4548 317.24 315.14 -1 -9.99 -0.99"
## [58] " 1958 7 1958.5370 315.86 315.18 -1 -9.99 -0.99"
## [59] " 1958 8 1958.6219 314.93 316.18 -1 -9.99 -0.99"
## [60] " 1958 9 1958.7068 313.20 316.08 -1 -9.99 -0.99"
## [61] " 1958 10 1958.7890 312.43 315.41 -1 -9.99 -0.99"
## [62] " 1958 11 1958.8740 313.33 315.20 -1 -9.99 -0.99"
## [63] " 1958 12 1958.9562 314.67 315.43 -1 -9.99 -0.99"
## [64] " 1959 1 1959.0411 315.58 315.55 -1 -9.99 -0.99"
## [65] " 1959 2 1959.1260 316.48 315.86 -1 -9.99 -0.99"
## [66] " 1959 3 1959.2027 316.65 315.38 -1 -9.99 -0.99"
## [67] " 1959 4 1959.2877 317.72 315.41 -1 -9.99 -0.99"
## [68] " 1959 5 1959.3699 318.29 315.49 -1 -9.99 -0.99"
## [69] " 1959 6 1959.4548 318.15 316.03 -1 -9.99 -0.99"
## [70] " 1959 7 1959.5370 316.54 315.86 -1 -9.99 -0.99"
## [71] " 1959 8 1959.6219 314.80 316.06 -1 -9.99 -0.99"
## [72] " 1959 9 1959.7068 313.84 316.73 -1 -9.99 -0.99"
## [73] " 1959 10 1959.7890 313.33 316.33 -1 -9.99 -0.99"
## [74] " 1959 11 1959.8740 314.81 316.68 -1 -9.99 -0.99"
## [75] " 1959 12 1959.9562 315.58 316.35 -1 -9.99 -0.99"
## [76] " 1960 1 1960.0410 316.43 316.40 -1 -9.99 -0.99"
## [77] " 1960 2 1960.1257 316.98 316.36 -1 -9.99 -0.99"
## [78] " 1960 3 1960.2049 317.58 316.28 -1 -9.99 -0.99"
## [79] " 1960 4 1960.2896 319.03 316.70 -1 -9.99 -0.99"
## [80] " 1960 5 1960.3716 320.04 317.22 -1 -9.99 -0.99"
## [81] " 1960 6 1960.4563 319.59 317.47 -1 -9.99 -0.99"
## [82] " 1960 7 1960.5383 318.18 317.52 -1 -9.99 -0.99"
## [83] " 1960 8 1960.6230 315.90 317.19 -1 -9.99 -0.99"
## [84] " 1960 9 1960.7077 314.17 317.08 -1 -9.99 -0.99"
## [85] " 1960 10 1960.7896 313.83 316.83 -1 -9.99 -0.99"
## [86] " 1960 11 1960.8743 315.00 316.88 -1 -9.99 -0.99"
## [87] " 1960 12 1960.9563 316.19 316.96 -1 -9.99 -0.99"
## [88] " 1961 1 1961.0411 316.89 316.86 -1 -9.99 -0.99"
## [89] " 1961 2 1961.1260 317.70 317.08 -1 -9.99 -0.99"
## [90] " 1961 3 1961.2027 318.54 317.26 -1 -9.99 -0.99"
## [91] " 1961 4 1961.2877 319.48 317.16 -1 -9.99 -0.99"
## [92] " 1961 5 1961.3699 320.58 317.76 -1 -9.99 -0.99"
## [93] " 1961 6 1961.4548 319.77 317.63 -1 -9.99 -0.99"
## [94] " 1961 7 1961.5370 318.57 317.88 -1 -9.99 -0.99"
## [95] " 1961 8 1961.6219 316.79 318.06 -1 -9.99 -0.99"
## [96] " 1961 9 1961.7068 314.99 317.90 -1 -9.99 -0.99"
## [97] " 1961 10 1961.7890 315.31 318.32 -1 -9.99 -0.99"
## [98] " 1961 11 1961.8740 316.10 317.99 -1 -9.99 -0.99"
## [99] " 1961 12 1961.9562 317.01 317.79 -1 -9.99 -0.99"
## [100] " 1962 1 1962.0411 317.94 317.91 -1 -9.99 -0.99"
## [101] " 1962 2 1962.1260 318.55 317.92 -1 -9.99 -0.99"
## [102] " 1962 3 1962.2027 319.68 318.39 -1 -9.99 -0.99"
## [103] " 1962 4 1962.2877 320.57 318.24 -1 -9.99 -0.99"
## [104] " 1962 5 1962.3699 321.02 318.18 -1 -9.99 -0.99"
## [105] " 1962 6 1962.4548 320.62 318.47 -1 -9.99 -0.99"
## [106] " 1962 7 1962.5370 319.61 318.92 -1 -9.99 -0.99"
## [107] " 1962 8 1962.6219 317.40 318.68 -1 -9.99 -0.99"
## [108] " 1962 9 1962.7068 316.25 319.17 -1 -9.99 -0.99"
## [109] " 1962 10 1962.7890 315.42 318.45 -1 -9.99 -0.99"
## [110] " 1962 11 1962.8740 316.69 318.58 -1 -9.99 -0.99"
## [111] " 1962 12 1962.9562 317.70 318.47 -1 -9.99 -0.99"
## [112] " 1963 1 1963.0411 318.74 318.70 -1 -9.99 -0.99"
## [113] " 1963 2 1963.1260 319.07 318.44 -1 -9.99 -0.99"
## [114] " 1963 3 1963.2027 319.86 318.57 -1 -9.99 -0.99"
## [115] " 1963 4 1963.2877 321.38 319.05 -1 -9.99 -0.99"
## [116] " 1963 5 1963.3699 322.25 319.40 -1 -9.99 -0.99"
## [117] " 1963 6 1963.4548 321.48 319.32 -1 -9.99 -0.99"
## [118] " 1963 7 1963.5370 319.74 319.05 -1 -9.99 -0.99"
## [119] " 1963 8 1963.6219 317.77 319.05 -1 -9.99 -0.99"
## [120] " 1963 9 1963.7068 316.21 319.14 -1 -9.99 -0.99"
## [121] " 1963 10 1963.7890 315.99 319.02 -1 -9.99 -0.99"
## [122] " 1963 11 1963.8740 317.07 318.97 -1 -9.99 -0.99"
## [123] " 1963 12 1963.9562 318.35 319.13 -1 -9.99 -0.99"
## [124] " 1964 1 1964.0410 319.57 319.54 -1 -9.99 -0.99"
## [125] " 1964 2 1964.1257 320.01 319.37 -1 -9.99 -0.99"
## [126] " 1964 3 1964.2049 320.74 319.41 -1 -9.99 -0.99"
## [127] " 1964 4 1964.2896 321.84 319.45 -1 -9.99 -0.99"
## [128] " 1964 5 1964.3716 322.26 319.40 -1 -9.99 -0.99"
## [129] " 1964 6 1964.4563 321.89 319.75 -1 -9.99 -0.99"
## [130] " 1964 7 1964.5383 320.44 319.77 -1 -9.99 -0.99"
## [131] " 1964 8 1964.6230 318.69 320.00 -1 -9.99 -0.99"
## [132] " 1964 9 1964.7077 316.70 319.66 -1 -9.99 -0.99"
## [133] " 1964 10 1964.7896 316.87 319.91 -1 -9.99 -0.99"
## [134] " 1964 11 1964.8743 317.68 319.58 -1 -9.99 -0.99"
## [135] " 1964 12 1964.9563 318.71 319.49 -1 -9.99 -0.99"
## [136] " 1965 1 1965.0411 319.44 319.40 -1 -9.99 -0.99"
## [137] " 1965 2 1965.1260 320.44 319.81 -1 -9.99 -0.99"
## [138] " 1965 3 1965.2027 320.89 319.59 -1 -9.99 -0.99"
## [139] " 1965 4 1965.2877 322.14 319.78 -1 -9.99 -0.99"
## [140] " 1965 5 1965.3699 322.17 319.30 -1 -9.99 -0.99"
## [141] " 1965 6 1965.4548 321.87 319.70 -1 -9.99 -0.99"
## [142] " 1965 7 1965.5370 321.21 320.51 -1 -9.99 -0.99"
## [143] " 1965 8 1965.6219 318.87 320.15 -1 -9.99 -0.99"
## [144] " 1965 9 1965.7068 317.81 320.77 -1 -9.99 -0.99"
## [145] " 1965 10 1965.7890 317.30 320.36 -1 -9.99 -0.99"
## [146] " 1965 11 1965.8740 318.87 320.78 -1 -9.99 -0.99"
## [147] " 1965 12 1965.9562 319.42 320.20 -1 -9.99 -0.99"
## [148] " 1966 1 1966.0411 320.62 320.59 -1 -9.99 -0.99"
## [149] " 1966 2 1966.1260 321.60 320.96 -1 -9.99 -0.99"
## [150] " 1966 3 1966.2027 322.39 321.08 -1 -9.99 -0.99"
## [151] " 1966 4 1966.2877 323.70 321.34 -1 -9.99 -0.99"
## [152] " 1966 5 1966.3699 324.08 321.20 -1 -9.99 -0.99"
## [153] " 1966 6 1966.4548 323.75 321.57 -1 -9.99 -0.99"
## [154] " 1966 7 1966.5370 322.38 321.68 -1 -9.99 -0.99"
## [155] " 1966 8 1966.6219 320.36 321.65 -1 -9.99 -0.99"
## [156] " 1966 9 1966.7068 318.64 321.60 -1 -9.99 -0.99"
## [157] " 1966 10 1966.7890 318.10 321.17 -1 -9.99 -0.99"
## [158] " 1966 11 1966.8740 319.78 321.70 -1 -9.99 -0.99"
## [159] " 1966 12 1966.9562 321.03 321.81 -1 -9.99 -0.99"
## [160] " 1967 1 1967.0411 322.33 322.29 -1 -9.99 -0.99"
## [161] " 1967 2 1967.1260 322.50 321.86 -1 -9.99 -0.99"
## [162] " 1967 3 1967.2027 323.04 321.73 -1 -9.99 -0.99"
## [163] " 1967 4 1967.2877 324.42 322.04 -1 -9.99 -0.99"
## [164] " 1967 5 1967.3699 325.00 322.12 -1 -9.99 -0.99"
## [165] " 1967 6 1967.4548 324.09 321.91 -1 -9.99 -0.99"
## [166] " 1967 7 1967.5370 322.54 321.84 -1 -9.99 -0.99"
## [167] " 1967 8 1967.6219 320.92 322.21 -1 -9.99 -0.99"
## [168] " 1967 9 1967.7068 319.25 322.23 -1 -9.99 -0.99"
## [169] " 1967 10 1967.7890 319.39 322.47 -1 -9.99 -0.99"
## [170] " 1967 11 1967.8740 320.73 322.65 -1 -9.99 -0.99"
## [171] " 1967 12 1967.9562 321.96 322.75 -1 -9.99 -0.99"
## [172] " 1968 1 1968.0410 322.57 322.54 -1 -9.99 -0.99"
## [173] " 1968 2 1968.1257 323.15 322.51 -1 -9.99 -0.99"
## [174] " 1968 3 1968.2049 323.89 322.55 -1 -9.99 -0.99"
## [175] " 1968 4 1968.2896 325.02 322.62 -1 -9.99 -0.99"
## [176] " 1968 5 1968.3716 325.57 322.68 -1 -9.99 -0.99"
## [177] " 1968 6 1968.4563 325.36 323.19 -1 -9.99 -0.99"
## [178] " 1968 7 1968.5383 324.14 323.46 -1 -9.99 -0.99"
## [179] " 1968 8 1968.6230 322.11 323.43 -1 -9.99 -0.99"
## [180] " 1968 9 1968.7077 320.33 323.32 -1 -9.99 -0.99"
## [181] " 1968 10 1968.7896 320.25 323.33 -1 -9.99 -0.99"
## [182] " 1968 11 1968.8743 321.32 323.25 -1 -9.99 -0.99"
## [183] " 1968 12 1968.9563 322.89 323.69 -1 -9.99 -0.99"
## [184] " 1969 1 1969.0411 324.00 323.97 -1 -9.99 -0.99"
## [185] " 1969 2 1969.1260 324.42 323.77 -1 -9.99 -0.99"
## [186] " 1969 3 1969.2027 325.63 324.31 -1 -9.99 -0.99"
## [187] " 1969 4 1969.2877 326.66 324.27 -1 -9.99 -0.99"
## [188] " 1969 5 1969.3699 327.38 324.48 -1 -9.99 -0.99"
## [189] " 1969 6 1969.4548 326.71 324.51 -1 -9.99 -0.99"
## [190] " 1969 7 1969.5370 325.88 325.17 -1 -9.99 -0.99"
## [191] " 1969 8 1969.6219 323.66 324.97 -1 -9.99 -0.99"
## [192] " 1969 9 1969.7068 322.38 325.37 -1 -9.99 -0.99"
## [193] " 1969 10 1969.7890 321.78 324.88 -1 -9.99 -0.99"
## [194] " 1969 11 1969.8740 322.86 324.79 -1 -9.99 -0.99"
## [195] " 1969 12 1969.9562 324.12 324.91 -1 -9.99 -0.99"
## [196] " 1970 1 1970.0411 325.06 325.03 -1 -9.99 -0.99"
## [197] " 1970 2 1970.1260 325.98 325.34 -1 -9.99 -0.99"
## [198] " 1970 3 1970.2027 326.93 325.61 -1 -9.99 -0.99"
## [199] " 1970 4 1970.2877 328.13 325.74 -1 -9.99 -0.99"
## [200] " 1970 5 1970.3699 328.08 325.16 -1 -9.99 -0.99"dfd <- read_table(here("data","nasa_carbon_dioxide.txt"), skip = 53, col_names = FALSE) #import the data with new column names, skip the first 53 lines and save it with the name dfd##
## -- Column specification --------------------------------------------------------
## cols(
## X1 = col_double(),
## X2 = col_double(),
## X3 = col_double(),
## X4 = col_double(),
## X5 = col_double(),
## X6 = col_double(),
## X7 = col_double(),
## X8 = col_double()
## )dfdnasa_co2 <- dfd %>% #save the name of the tibble
unite(df3, X1,X2, sep = " ")%>% #unite the columns X1 and X2 with a new name df3
rename(date = df3)%>% #rename df3 as date
rename(co2 = X4) %>% #rename X4 as co2
select(c(date,co2))%>% #select the columns date and co2
mutate(date = parse_date(date, format = "%Y %m")) #create a new column and turn date as date with format year and month
ggplot() + #create a plot
layer (
data = nasa_co2, #use the data from nasa_co2
geom = "point",
mapping = aes(x = date, y = co2, colour = date), #specifies the data that we use in each axis
stat = "identity", #no further transformation
position = "identity" #position adjustment
) + scale_y_continuous(limits = c(300,400)) #numbered axis Y from 300 to 400## Warning: Removed 83 rows containing missing values (geom_point).
#Question 1e
nasa <- nasa_temp %>% #save the name of the tibble
full_join( #merge the data sets along rows
nasa_ice, #the tibble we want to combine
by = "date", #combine based the date
keep = FALSE) %>% #don't preserved the keys from x and y in the output
full_join(
nasa_sea,
by = "date",
keep = FALSE) %>%
full_join(
nasa_co2,
by = "date",
keep = FALSE)
nasa#Question 1f
nasa %>% #name the nasa tibble df_temp
filter(date >= "1960-01-01" & year <= "2020-01-01") %>% #select the years from 1960 - 2020
ggplot(mapping = aes(y = co2, x = temp)) + #define the axes
geom_point(mapping = aes(colour = date)) #add colour by year## Error: Problem with `filter()` input `..1`.
## i Input `..1` is `date >= "1960-01-01" & year <= "2020-01-01"`.
## x comparison (4) is possible only for atomic and list typesdf_temp## Error in eval(expr, envir, enclos): object 'df_temp' not found#Question 2a
read_lines(file = here("data","luthi_carbon_dioxide.txt"), n_max = 800L ) #read the first 800 lines## [1] "EPICA Dome C Ice Core 800KYr Carbon Dioxide Data"
## [2] "-----------------------------------------------------------------------"
## [3] " World Data Center for Paleoclimatology, Boulder"
## [4] " and"
## [5] " NOAA Paleoclimatology Program"
## [6] "-----------------------------------------------------------------------"
## [7] "NOTE: PLEASE CITE ORIGINAL REFERENCE WHEN USING THIS DATA!!!!!"
## [8] ""
## [9] ""
## [10] "NAME OF DATA SET: EPICA Dome C Ice Core 800KYr Carbon Dioxide Data"
## [11] "LAST UPDATE: 6/2008 (Original receipt by WDC Paleo)"
## [12] "CONTRIBUTORS: Dieter Luthi, et al."
## [13] "IGBP PAGES/WDCA CONTRIBUTION SERIES NUMBER: 2008-055"
## [14] ""
## [15] "WDC PALEO CONTRIBUTION SERIES CITATION: "
## [16] "Luthi, D., et al.. 2008."
## [17] "EPICA Dome C Ice Core 800KYr Carbon Dioxide Data. "
## [18] "IGBP PAGES/World Data Center for Paleoclimatology "
## [19] "Data Contribution Series # 2008-055. "
## [20] "NOAA/NCDC Paleoclimatology Program, Boulder CO, USA."
## [21] ""
## [22] ""
## [23] "ORIGINAL REFERENCE: "
## [24] "Luthi, D., M. Le Floch, B. Bereiter, T. Blunier, J.-M. Barnola, "
## [25] "U. Siegenthaler, D. Raynaud, J. Jouzel, H. Fischer, K. Kawamura, "
## [26] "and T.F. Stocker. 2008."
## [27] "High-resolution carbon dioxide concentration record 650,000-800,000 "
## [28] "years before present."
## [29] "Nature, Vol. 453, pp. 379-382, 15 May 2008. doi:10.1038/nature06949"
## [30] ""
## [31] "ABSTRACT:"
## [32] "Changes in past atmospheric carbon dioxide concentrations can"
## [33] "be determined by measuring the composition of air trapped in ice"
## [34] "cores from Antarctica. So far, the Antarctic Vostok and EPICA"
## [35] "Dome C ice cores have provided a composite record of atmospheric"
## [36] "carbon dioxide levels over the past 650,000 years. Here we present "
## [37] "results of the lowest 200m of the Dome C ice core, extending "
## [38] "the record of atmospheric carbon dioxide concentration by two "
## [39] "complete glacial cycles to 800,000 yr before present. From "
## [40] "previously published data and the present work, we find that"
## [41] "atmospheric carbon dioxide is strongly correlated with Antarctic"
## [42] "temperature throughout eight glacial cycles but with significantly"
## [43] "lower concentrations between 650,000 and 750,000 yr before present."
## [44] "Carbon dioxide levels are below 180 parts per million by volume "
## [45] "(p.p.m.v.) for a period of 3,000 yr during Marine Isotope Stage 16, "
## [46] "possibly reflecting more pronounced oceanic carbon storage. "
## [47] "We report the lowest carbon dioxide concentration measured"
## [48] "in an ice core, which extends the pre-industrial range of"
## [49] "carbon dioxide concentrations during the late Quaternary by"
## [50] "about 10 p.p.m.v. to 172-300 p.p.m.v."
## [51] ""
## [52] ""
## [53] "ADDITIONAL REFERENCES:"
## [54] "Indermuhle, A., E. Monnin, B. Stauffer, T.F. Stocker, M. Wahlen, 1999, "
## [55] "Atmospheric CO2 concentration from 60 to 20 kyr BP from the "
## [56] "Taylor Dome ice core, Antarctica. Geophysical Research Letters, 27, 735-738."
## [57] ""
## [58] "Monnin, E., A. Indermuhle, A. Dallenbach, J. Fluckiger, B. Stauffer, "
## [59] "T.F. Stocker, D. Raynaud, and J.-M. Barnola. 2001. "
## [60] "Atmospheric CO2 concentrations over the last glacial termination. "
## [61] "Science, Vol. 291, pp. 112-114."
## [62] ""
## [63] "Petit, J.R., J. Jouzel, D. Raynaud, N.I. Barkov, J.-M. Barnola, "
## [64] "I. Basile, M. Benders, J. Chappellaz, M. Davis, G. Delayque, "
## [65] "M. Delmotte, V.M. Kotlyakov, M. Legrand, V.Y. Lipenkov, "
## [66] "C. Lorius, L. Pepin, C. Ritz, E. Saltzman, and M. Stievenard. 1999. "
## [67] "Climate and atmospheric history of the past 420,000 years from "
## [68] "the Vostok ice core, Antarctica. "
## [69] "Nature 399: 429-436."
## [70] ""
## [71] "Siegenthaler, U., T.F. Stocker, E. Monnin, D. Luthi, J. Schwander, B. Stauffer, "
## [72] "D. Raynaud, J.-M. Barnola, H. Fischer, V. Masson-Delmotte, J. Jouzel. 2005. "
## [73] "Stable Carbon Cycle-Climate Relationship During the Late Pleistocene."
## [74] "Science, v. 310 , pp. 1313-1317, 25 November 2005."
## [75] ""
## [76] ""
## [77] ""
## [78] "GEOGRAPHIC REGION: East Antarctica"
## [79] "PERIOD OF RECORD: 800 KYrBP -present"
## [80] ""
## [81] "FUNDING SOURCES: "
## [82] "This work is a contribution to the European Project for Ice Coring "
## [83] "in Antarctica (EPICA), a joint European Science Foundation/European"
## [84] "Commission scientific program, funded by the European Commission and "
## [85] "by national contributions from Belgium, Denmark, France, Germany, "
## [86] "Italy, the Netherlands, Norway, Sweden, Switzerland and the "
## [87] "United Kingdom. We acknowledge financial support by the Swiss NSF, "
## [88] "the University of Bern, the Swiss Federal Agency of Energy and the "
## [89] "French ANR (Agence nationale pour la Recherche; programme PICC)."
## [90] ""
## [91] ""
## [92] "DESCRIPTION: "
## [93] "Carbon dioxide record from the EPICA (European Project for Ice Coring "
## [94] "in Antarctica) Dome C ice core covering 0 to 800 kyr BP. "
## [95] ""
## [96] "EPICA Dome C ice core location: 75 06'S, 123 21'E, 3233m above sea level "
## [97] ""
## [98] ""
## [99] "These data also available from the Nature Supplementary Materials for "
## [100] "Luthi et al. (2008). "
## [101] ""
## [102] "NOTE: These data have been revised for an analytical bias as described "
## [103] "by Bereiter et al. 2015. Please see the revised EDC and Antarctic "
## [104] "composite CO2 records at: http://www.ncdc.noaa.gov/paleo/study/17975"
## [105] ""
## [106] ""
## [107] ""
## [108] ""
## [109] "DATA:"
## [110] "1. EDC Carbon Dioxide Data (611-800 kyr BP), Luthi et al. (2008)"
## [111] "(Additional EDC and Antarctic Ice Core CO2 data and composite CO2 record are below)"
## [112] ""
## [113] "Column 1: Depth (m)"
## [114] "Column 2: Age (EDC3_gas_a) years BP"
## [115] "Column 3: CO2 (ppmv) measured at University of Bern "
## [116] "Column 4: CO2 sigma error (ppmv) measured at University of Bern "
## [117] "Column 5: Depth (m)"
## [118] "Column 6: Age (EDC3_gas_a) years BP"
## [119] "Column 7: CO2 (ppmv) measured at LGGE in Grenoble "
## [120] ""
## [121] ""
## [122] ""
## [123] " University of Bern LGGE in Grenoble"
## [124] "Depth Age CO2 sigma Depth Age CO2 "
## [125] "3026.58 611269 257.8 2.1 3061.71 667435 178.5"
## [126] "3030.97 616164 252.6 0.6 3063.98 670124 189.0"
## [127] "3036.44 623109 243.3 2.8 3085.78 688035 234.0"
## [128] "3040.87 630183 204.4 0.9 3086.88 688751 235.4"
## [129] "3043.07 635364 195.0 1.5 3087.98 689444 241.0"
## [130] "3055.18 658404 187.5 1.8 3089.08 690155 235.0"
## [131] "3056.25 659983 185.6 1.1 3091.28 691524 235.9"
## [132] "3057.36 661563 192.1 1.0 3093.48 692857 236.3"
## [133] "3058.47 663133 192.0 2.1 3120.01 715603 223.8"
## [134] "3059.55 664597 190.6 1.3 3122.20 718581 190.2"
## [135] "3060.33 665645 178.2 1.1 3124.41 721870 217.0"
## [136] "3060.73 666174 178.5 1.1 3128.68 727458 203.7"
## [137] "3061.36 666995 172.7 1.0 3133.08 732300 210.7"
## [138] "3061.82 667569 171.6 1.4 3135.28 734408 209.6"
## [139] "3062.53 668447 175.6 0.7 3141.82 739986 198.0"
## [140] "3062.93 668934 178.5 0.7 3146.37 744681 185.2"
## [141] "3063.64 669751 185.5 0.2 3150.68 749152 188.8"
## [142] "3064.02 670176 189.3 0.9 3152.88 751552 193.8"
## [143] "3064.76 670916 192.6 1.0 3155.08 754124 197.3"
## [144] "3065.12 671286 194.6 0.7 3156.18 755354 203.4"
## [145] "3065.76 671926 192.5 0.6 3157.28 756605 214.4"
## [146] "3066.22 672386 194.8 1.0 3158.38 757805 225.5"
## [147] "3066.93 673095 198.7 1.0 3159.48 759027 216.6"
## [148] "3067.33 673475 202.3 0.7 3160.58 760338 214.9"
## [149] "3068.07 674173 209.2 0.6 3161.68 761745 213.0"
## [150] "3068.42 674521 213.7 0.8 3162.78 763158 221.3"
## [151] "3069.52 675589 220.0 0.8 3163.88 764529 226.5"
## [152] "3070.16 676170 217.4 0.6 3164.98 765917 216.1"
## [153] "3070.62 676524 214.0 0.9 3167.18 768940 227.5"
## [154] "3071.33 677068 215.6 1.4 3168.28 770434 233.9"
## [155] "3071.72 677380 217.4 1.5 3169.38 771888 226.9"
## [156] "3072.44 677984 226.5 0.8 3170.48 773353 238.6"
## [157] "3072.80 678291 230.0 0.9 3171.58 774854 240.1"
## [158] "3073.53 678914 230.8 0.6 3172.68 776322 245.9"
## [159] "3073.93 679252 230.3 1.2 3173.78 777719 246.7"
## [160] "3074.56 679732 223.0 1.2 3174.88 779076 243.8"
## [161] "3075.02 680081 225.0 1.3 3177.08 781771 251.2"
## [162] "3075.73 680608 218.4 0.9 3178.18 783110 252.5"
## [163] "3076.13 680920 216.2 1.0 3179.28 784409 248.4"
## [164] "3076.85 681531 217.3 1.7 3180.38 785654 255.3"
## [165] "3077.23 681849 219.7 0.6 3181.48 786819 256.6"
## [166] "3077.93 682446 222.6 1.6 3182.58 787957 246.4"
## [167] "3078.32 682762 221.3 1.3 3183.68 789126 239.3"
## [168] "3078.96 683262 218.7 0.8 3185.88 791767 217.3"
## [169] "3079.43 683612 217.5 0.7 3186.98 793255 224.2"
## [170] "3080.14 684142 217.5 1.4 3188.08 794949 206.7"
## [171] "3080.52 684419 219.4 1.0 3190.28 798893 193.6"
## [172] "3081.25 684949 219.5 1.1"
## [173] "3081.63 685217 219.7 1.2"
## [174] "3082.34 685716 223.5 1.0"
## [175] "3082.72 685980 224.4 1.3"
## [176] "3083.37 686425 224.3 1.1"
## [177] "3083.82 686726 227.3 1.7"
## [178] "3084.56 687227 228.7 1.3"
## [179] "3084.92 687470 228.8 1.5"
## [180] "3085.65 687949 232.3 1.0"
## [181] "3086.03 688195 233.0 0.5"
## [182] "3086.73 688652 235.8 1.1"
## [183] "3087.08 688881 234.9 1.2"
## [184] "3087.76 689304 235.8 2.0"
## [185] "3088.23 689603 239.9 0.6"
## [186] "3088.93 690057 235.6 1.3"
## [187] "3089.30 690294 234.8 2.1"
## [188] "3090.05 690771 240.0 2.1"
## [189] "3090.42 690999 234.0 0.8"
## [190] "3091.13 691432 235.6 1.0"
## [191] "3091.52 691672 236.6 0.7"
## [192] "3092.16 692057 235.5 0.9"
## [193] "3092.62 692338 235.9 1.4"
## [194] "3093.33 692765 232.9 0.6"
## [195] "3093.70 692990 234.8 1.5"
## [196] "3094.45 693433 234.1 1.5"
## [197] "3094.80 693639 234.1 1.3"
## [198] "3095.53 694068 235.4 1.0"
## [199] "3095.92 694300 234.4 1.1"
## [200] "3096.56 694672 235.8 1.3"
## [201] "3097.02 694941 236.9 0.8"
## [202] "3097.74 695383 236.7 1.9"
## [203] "3098.13 695618 237.6 0.7"
## [204] "3098.85 696062 234.6 1.0"
## [205] "3099.22 696287 234.8 0.6"
## [206] "3099.93 696717 235.4 0.8"
## [207] "3100.32 696963 232.9 0.6"
## [208] "3100.92 697331 232.4 0.7"
## [209] "3101.43 697660 232.2 0.5"
## [210] "3102.13 698120 231.0 1.0"
## [211] "3102.52 698386 228.0 0.5"
## [212] "3103.25 698880 226.4 1.0"
## [213] "3103.57 699102 227.7 0.7"
## [214] "3104.33 699633 227.6 1.6"
## [215] "3104.71 699909 226.0 0.3"
## [216] "3105.36 700389 228.7 1.3"
## [217] "3105.82 700744 227.6 1.1"
## [218] "3106.46 701242 228.2 0.5"
## [219] "3106.92 701606 228.8 1.4"
## [220] "3107.64 702158 229.3 0.5"
## [221] "3107.93 702381 230.3 1.7"
## [222] "3108.65 702988 232.4 1.3"
## [223] "3109.12 703384 232.8 1.6"
## [224] "3109.75 703934 231.2 1.8"
## [225] "3110.07 704211 231.2 0.9"
## [226] "3110.88 704973 233.9 0.8"
## [227] "3111.32 705410 228.5 1.5"
## [228] "3112.05 706141 228.6 1.0"
## [229] "3112.31 706409 228.1 1.0"
## [230] "3115.25 709680 219.7 0.6"
## [231] "3115.72 710237 220.2 0.3"
## [232] "3116.42 711104 218.9 1.5"
## [233] "3116.68 711421 218.7 1.4"
## [234] "3117.81 712833 218.5 0.5"
## [235] "3118.60 713843 222.3 1.6"
## [236] "3118.95 714288 221.7 2.0"
## [237] "3119.67 715180 217.7 0.6"
## [238] "3120.12 715750 222.1 0.6"
## [239] "3120.85 716704 208.1 0.7"
## [240] "3121.13 717065 205.0 1.7"
## [241] "3121.86 718064 192.9 1.2"
## [242] "3122.32 718779 184.3 1.1"
## [243] "3122.95 719794 187.8 1.6"
## [244] "3123.35 720337 195.2 0.8"
## [245] "3124.06 721318 206.3 0.8"
## [246] "3124.52 722039 211.3 0.9"
## [247] "3125.27 723133 213.4 1.2"
## [248] "3125.53 723464 213.2 1.3"
## [249] "3126.27 724445 210.3 2.0"
## [250] "3126.72 725059 206.3 0.7"
## [251] "3127.41 725937 206.6 1.8"
## [252] "3127.73 726322 208.1 1.2"
## [253] "3128.45 727192 204.5 0.4"
## [254] "3128.91 727732 205.5 1.3"
## [255] "3129.62 728568 205.1 1.1"
## [256] "3129.93 728921 205.4 0.8"
## [257] "3131.12 730299 204.0 1.6"
## [258] "3131.75 730949 204.1 0.8"
## [259] "3132.13 731329 204.9 0.8"
## [260] "3132.92 732141 203.8 1.0"
## [261] "3133.32 732548 205.9 1.7"
## [262] "3134.02 733261 203.9 0.7"
## [263] "3134.33 733543 204.4 0.3"
## [264] "3135.06 734223 205.3 0.4"
## [265] "3135.52 734604 207.4 1.9"
## [266] "3136.19 735167 201.7 1.2"
## [267] "3136.53 735459 201.3 0.8"
## [268] "3137.25 736079 204.1 1.0"
## [269] "3137.72 736460 209.7 1.8"
## [270] "3138.44 737034 208.1 0.7"
## [271] "3138.73 737266 211.3 0.8"
## [272] "3139.46 737889 210.6 1.4"
## [273] "3139.89 738272 206.5 1.7"
## [274] "3140.54 738844 200.3 1.6"
## [275] "3140.88 739137 197.8 1.5"
## [276] "3141.66 739842 185.0 0.9"
## [277] "3142.12 740277 178.9 0.3"
## [278] "3142.85 741021 178.6 2.4"
## [279] "3143.13 741307 176.6 2.4"
## [280] "3143.86 742075 177.9 2.1"
## [281] "3144.32 742558 182.3 1.3"
## [282] "3144.98 743233 181.7 2.7"
## [283] "3145.32 743589 180.4 0.7"
## [284] "3146.06 744354 181.2 0.9"
## [285] "3146.52 744843 182.0 0.9"
## [286] "3147.48 745836 180.2 1.2"
## [287] "3148.26 746643 183.1 0.4"
## [288] "3148.72 747110 180.8 0.3"
## [289] "3149.35 747759 180.8 1.3"
## [290] "3149.68 748101 180.4 0.8"
## [291] "3150.45 748913 181.4 1.3"
## [292] "3150.91 749401 182.9 1.8"
## [293] "3151.65 750194 184.8 1.6"
## [294] "3151.91 750476 184.0 1.4"
## [295] "3152.65 751301 186.2 1.9"
## [296] "3153.12 751830 190.1 1.3"
## [297] "3153.78 752605 188.0 0.3"
## [298] "3154.10 752978 196.5 1.8"
## [299] "3154.96 753984 191.5 1.7"
## [300] "3155.32 754394 195.8 1.5"
## [301] "3156.08 755241 200.5 2.0"
## [302] "3156.30 755495 201.9 1.4"
## [303] "3157.05 756357 206.0 2.2"
## [304] "3157.52 756871 210.7 2.3"
## [305] "3158.15 757561 215.0 1.5"
## [306] "3158.53 757962 219.2 1.4"
## [307] "3158.80 758259 215.3 0.7"
## [308] "3159.00 758475 217.6 1.8"
## [309] "3159.35 758883 217.9 2.3"
## [310] "3159.72 759306 214.9 1.2"
## [311] "3160.47 760202 208.8 0.8"
## [312] "3160.71 760500 206.9 1.1"
## [313] "3161.46 761453 206.1 1.9"
## [314] "3161.92 762064 212.0 0.2"
## [315] "3162.55 762871 216.0 2.1"
## [316] "3162.91 763319 215.0 0.9"
## [317] "3163.20 763686 225.7 3.0"
## [318] "3163.40 763934 221.4 2.7"
## [319] "3163.65 764249 224.1 1.4"
## [320] "3164.12 764833 222.6 0.9"
## [321] "3164.84 765735 216.8 1.6"
## [322] "3165.13 766110 215.7 0.5"
## [323] "3165.86 767096 213.5 0.4"
## [324] "3166.32 767737 217.7 0.9"
## [325] "3166.97 768655 222.4 2.1"
## [326] "3167.26 769050 221.4 1.8"
## [327] "3167.60 769514 228.1 1.6"
## [328] "3167.80 769787 226.0 1.6"
## [329] "3168.05 770133 231.5 1.9"
## [330] "3168.29 770447 235.6 1.1"
## [331] "3168.50 770724 238.2 2.2"
## [332] "3168.70 770994 235.6 2.1"
## [333] "3168.90 771260 237.7 2.4"
## [334] "3169.24 771708 229.5 1.5"
## [335] "3169.53 772076 230.9 1.0"
## [336] "3170.25 773043 230.0 2.3"
## [337] "3170.72 773680 233.3 0.9"
## [338] "3171.35 774548 236.9 0.4"
## [339] "3171.73 775051 240.5 0.6"
## [340] "3172.46 776037 238.8 2.0"
## [341] "3172.92 776636 243.9 0.7"
## [342] "3173.65 777556 246.3 0.5"
## [343] "3173.93 777900 246.1 1.1"
## [344] "3174.65 778798 245.8 2.4"
## [345] "3175.11 779364 243.9 0.9"
## [346] "3175.84 780268 248.5 0.6"
## [347] "3176.13 780612 242.8 0.7"
## [348] "3176.89 781535 248.7 0.7"
## [349] "3177.32 782059 246.2 1.1"
## [350] "3178.31 783263 252.1 2.5"
## [351] "3179.05 784147 246.9 0.7"
## [352] "3179.52 784692 250.7 0.2"
## [353] "3180.15 785413 253.3 2.6"
## [354] "3180.51 785789 255.4 1.4"
## [355] "3181.26 786587 260.3 1.3"
## [356] "3181.73 787076 256.9 0.7"
## [357] "3182.43 787805 248.1 1.5"
## [358] "3182.65 788033 247.9 2.7"
## [359] "3183.46 788887 229.5 0.8"
## [360] "3183.91 789381 226.3 3.0"
## [361] "3184.57 790153 218.2 0.8"
## [362] "3184.90 790538 221.3 1.8"
## [363] "3185.66 791491 215.4 3.7"
## [364] "3186.12 792081 205.1 2.5"
## [365] "3186.75 792943 204.0 1.6"
## [366] "3186.98 793260 209.0 1.9"
## [367] "3187.87 794608 199.4 1.7"
## [368] "3188.23 795202 195.2 2.0"
## [369] "3188.98 796467 189.3 2.1"
## [370] "3189.33 797099 188.4 1.4"
## [371] "3190.08 798512 191.0 2.2"
## [372] ""
## [373] ""
## [374] ""
## [375] ""
## [376] "2. Antarctic CO2 data from Vostok, Dome C, and Taylor Dome"
## [377] "Depth in meters, CO2 and sigma in ppmv, Gas age scale: EDC3_gas_a (tentatively synchronized for Taylor Dome)"
## [378] ""
## [379] "Dome C (0-22 kyr BP) Vostok (0-440 kyr BP) Taylor Dome (19-63 kyr BP) Dome C (393-664 kyr BP) Dome C (611-800 kyr BP)"
## [380] "Monnin et al. (2001) Petit et al. (1999) Indermuhle et al. (2000) Siegenthaler et al. (2005) Luthi et al. (sub)"
## [381] " Pepin et al. (2001)"
## [382] " Raynaud et al. (2005)"
## [383] "measured at:"
## [384] "University of Bern LGGE in Grenoble University of Bern University of Bern LGGE in Grenoble University of Bern LGGE in Grenoble"
## [385] "Depth EDC3_gas_a CO2 sigma Depth EDC3_gas_a CO2 Depth Age(tentative) CO2 sigma Depth EDC3_gas_a CO2 sigma Depth EDC3_gas_a CO2 Depth EDC3_gas_a CO2 sigma Depth EDC3_gas_a CO2 "
## [386] "102.83 137 280.4 1.8 149.1 2690 284.7 380.82 18906 190.5 1 2761.85 415717 276.4 1.6 2700.77 392544 259.5 3026.58 611269 257.8 2.1 3061.71 667435 178.5"
## [387] "106.89 268 274.9 0.7 173.1 3897 272.7 382.42 23379 189.1 0.5 2762.89 416193 271.7 1.2 2702.97 393579 273.6 3030.97 616164 252.6 0.6 3063.98 670124 189.0"
## [388] "107.20 279 277.9 0.7 177.4 4124 268.1 382.76 24011 189 1.4 2765.08 417191 273.4 1.5 2705.17 394560 260.7 3036.44 623109 243.3 2.8 3085.78 688035 234.0"
## [389] "110.25 395 279.1 1.3 228.6 6735 262.2 383.54 25337 187.7 1 2766.18 417698 271.8 1.7 2713.97 398086 276.3 3040.87 630183 204.4 0.9 3086.88 688751 235.4"
## [390] "110.50 404 281.9 1.1 250.3 7873 254.5 385.33 27507 195.2 0.5 2767.33 418245 274.6 1.8 2718.37 399722 277.1 3043.07 635364 195.0 1.5 3087.98 689444 241.0"
## [391] "113.27 485 277.7 0.7 266 8670 259.6 385.64 27781 194.1 0.4 2769.48 419260 273.7 0.8 2720.57 400504 283.2 3055.18 658404 187.5 1.8 3089.08 690155 235.0"
## [392] "115.48 559 281.1 1.1 302.6 10167 261.6 386.62 28527 196.1 0.7 2770.58 419808 271.2 1.5 2724.97 402000 283.1 3056.25 659983 185.6 1.1 3091.28 691524 235.9"
## [393] "118.62 672 282.2 0.5 321.2 10983 263.7 387.66 29238 194 0.6 2771.68 420350 273.8 1.6 2727.17 402731 275.7 3057.36 661563 192.1 1.0 3093.48 692857 236.3"
## [394] "121.50 754 280.1 0.6 331.6 11422 244.8 388.52 29772 191.1 0.5 2773.88 421484 268.6 1.4 2731.57 404181 276.5 3058.47 663133 192.0 2.1 3120.01 715603 223.8"
## [395] "124.82 877 278.4 1.5 342.1 11881 238.3 389.7 30407 193.5 0.8 2774.96 422074 266.4 1.8 2733.77 404927 280.5 3059.55 664597 190.6 1.3 3122.20 718581 190.2"
## [396] "127.02 950 276.6 1.4 365.5 13356 236.2 390.71 30881 196.8 0.5 2776.13 422649 270.6 1.1 2738.17 406368 279.6 3060.33 665645 178.2 1.1 3124.41 721870 217.0"
## [397] "129.75 1060 279.1 1 375.6 14010 225.2 391.63 31308 199.6 0.6 2778.28 423764 267.7 2.9 2740.37 407093 285.6 3060.73 666174 178.5 1.1 3128.68 727458 203.7"
## [398] "132.50 1153 277.7 1.2 443.5 20023 182.2 392.62 31700 199.1 0.2 2779.39 424332 268.3 1.9 2744.77 408600 284.5 3061.36 666995 172.7 1.0 3133.08 732300 210.7"
## [399] "134.72 1233 278.7 1.2 470.8 22827 189.2 393.55 32090 200.4 0.6 2780.48 424840 270.8 1.1 2746.97 409383 275.2 3061.82 667569 171.6 1.4 3135.28 734408 209.6"
## [400] "138.02 1350 277.4 0.8 506.4 25994 191.6 395.32 32771 200.2 0.3 2781.32 425242 270.0 2.5 2746.97 409383 274.2 3062.53 668447 175.6 0.7 3141.82 739986 198.0"
## [401] "141.30 1453 279.2 0.9 544.7 29063 188.5 396.42 33161 200.1 0.7 2781.96 425569 265.4 2.0 2749.17 410206 282.6 3062.93 668934 178.5 0.7 3146.37 744681 185.2"
## [402] "144.05 1552 280.0 0.8 554.2 30020 191.7 396.98 33341 201.6 0.5 2782.73 425975 255.3 1.3 2751.37 411071 283.5 3063.64 669751 185.5 0.2 3150.68 749152 188.8"
## [403] "146.27 1638 278.9 0.8 602.3 35009 205.3 397.64 33580 200.9 0.6 2783.81 426598 252.1 0.7 2755.77 412962 274.9 3064.02 670176 189.3 0.9 3152.88 751552 193.8"
## [404] "149.02 1733 278.7 0.7 625.6 37471 209.1 398.61 33913 203.6 0.4 2784.88 427285 248.2 0.9 2757.97 413948 264.9 3064.76 670916 192.6 1.0 3155.08 754124 197.3"
## [405] "151.20 1812 278.0 1.2 700.2 43500 209.1 400.02 34364 205.3 0.6 2785.27 427566 242.5 1.5 2760.17 414963 271.6 3065.12 671286 194.6 0.7 3156.18 755354 203.4"
## [406] "154.50 1931 276.9 0.7 765 47336 189.3 405.53 36061 208.8 0.3 2787.08 429006 219.7 1.7 2762.37 415955 276.2 3065.76 671926 192.5 0.6 3157.28 756605 214.4"
## [407] "157.82 2057 276.7 0.8 788.2 48854 188.4 406.6 36378 213 0.8 2788.03 429876 227.2 2.2 2764.57 416965 268.5 3066.22 672386 194.8 1.0 3158.38 757805 225.5"
## [408] "160.03 2128 276.7 0.8 800 49690 210.1 407.73 36695 211.3 0.7 2789.29 431063 211.5 1.7 2766.77 417979 277.7 3066.93 673095 198.7 1.0 3159.48 759027 216.6"
## [409] "162.17 2212 277.6 1.3 812.2 50663 215.7 408.54 36883 212.6 1.1 2789.67 431445 207.6 1.3 2768.97 419013 273.3 3067.33 673475 202.3 0.7 3160.58 760338 214.9"
## [410] "165.52 2334 277.9 0.5 834.8 52382 190.4 411.31 37545 213.6 0.6 2790.78 432599 209.8 1.6 2771.17 420107 268.9 3068.07 674173 209.2 0.6 3161.68 761745 213.0"
## [411] "168.28 2433 273.9 1.1 902.2 57088 221.7 412.24 37740 210.8 0.4 2791.87 433674 207.5 1.3 2775.57 422374 276.6 3068.42 674521 213.7 0.8 3162.78 763158 221.3"
## [412] "171.00 2536 278.9 0.6 912 57657 210.4 413.11 37949 209.9 0.7 2792.97 434804 200.3 1.6 2775.57 422374 274.3 3069.52 675589 220.0 0.8 3163.88 764529 226.5"
## [413] "173.14 2604 275.3 1.6 986.2 62859 195.3 413.97 38149 210.6 0.5 2794.08 435989 201.7 1.6 2777.77 423491 270.9 3070.16 676170 217.4 0.6 3164.98 765917 216.1"
## [414] "176.52 2728 274.7 1.2 1011.3 64939 191.4 416.37 38679 210.3 0.7 2795.17 437152 201.3 1.1 2779.97 424604 273.7 3070.62 676524 214.0 0.9 3167.18 768940 227.5"
## [415] "178.72 2806 276.3 0.9 1023.5 65939 194.9 416.99 38826 207.8 0.6 2796.28 438356 202.0 1.5 2782.17 425678 257.7 3071.33 677068 215.6 1.4 3168.28 770434 233.9"
## [416] "181.45 2902 274.6 0.8 1087.2 71049 227.3 418.27 39100 205.7 0.8 2797.38 439565 199.1 1.1 2784.37 426953 254.1 3071.72 677380 217.4 1.5 3169.38 771888 226.9"
## [417] "185.85 3053 276.3 1.5 1112.5 73227 229.1 419.39 39345 198.6 0.5 2798.92 441220 201.1 0.9 3072.44 677984 226.5 0.8 3170.48 773353 238.6"
## [418] "187.52 3116 273.1 1.1 1162.1 77150 217.1 420.31 39527 196.4 0.8 2800.02 442411 203.5 0.6 3072.80 678291 230.0 0.9 3171.58 774854 240.1"
## [419] "189.72 3215 274.0 0.3 1175 78183 221.7 422.53 39960 197.5 0.8 2801.13 443562 208.1 1.8 3073.53 678914 230.8 0.6 3172.68 776322 245.9"
## [420] "193.00 3336 275.0 0.6 1209.9 80614 230.9 424.75 40427 198.2 0.3 2802.21 444650 201.7 1.7 3073.93 679252 230.3 1.2 3173.78 777719 246.7"
## [421] "196.30 3453 273.4 1.3 1237.2 82417 241.1 426.46 40837 201.4 0.8 2803.33 445829 201.2 2.1 3074.56 679732 223.0 1.2 3174.88 779076 243.8"
## [422] "198.52 3523 273.0 0.8 1251.5 83333 236.4 427.06 40990 198.9 0.7 2804.42 446984 204.9 1.4 3075.02 680081 225.0 1.3 3177.08 781771 251.2"
## [423] "201.28 3622 271.5 1 1261.2 84016 228.0 429.3 41620 201.4 0.7 2805.52 448103 201.9 1.8 3075.73 680608 218.4 0.9 3178.18 783110 252.5"
## [424] "204.00 3721 275.4 0.5 1274.2 85020 214.2 430.13 41895 201.6 0.6 2806.62 449244 198.4 1.3 3076.13 680920 216.2 1.0 3179.28 784409 248.4"
## [425] "206.20 3790 274.9 1.3 1289.2 86181 217.0 430.83 42131 202.2 0.9 2807.72 450455 193.3 1.6 3076.85 681531 217.3 1.7 3180.38 785654 255.3"
## [426] "209.52 3910 271.7 1 1309.2 87917 208.0 431.52 42342 201.9 1 2808.82 451593 192.5 1.0 3077.23 681849 219.7 0.6 3181.48 786819 256.6"
## [427] "212.27 4004 271.6 0.7 1338.2 90357 224.2 434.75 43252 199.9 0.7 2809.46 452283 199.1 0.6 3077.93 682446 222.6 1.6 3182.58 787957 246.4"
## [428] "215.00 4096 272.8 0.8 1349 91249 228.3 436.05 43612 201.7 0.8 2809.93 452795 204.3 1.0 3078.32 682762 221.3 1.3 3183.68 789126 239.3"
## [429] "216.65 4161 271.5 0.9 1387.2 94353 232.0 436.93 43879 205 0.6 2810.56 453514 203.3 1.0 3078.96 683262 218.7 0.8 3185.88 791767 217.3"
## [430] "221.05 4324 271.1 0.8 1451.5 99849 225.8 438.21 44239 210 0.6 2811.01 454023 208.3 1.4 3079.43 683612 217.5 0.7 3186.98 793255 224.2"
## [431] "222.72 4374 269.1 0.6 1463.2 100837 230.8 438.92 44439 214 0.8 2812.12 455279 202.4 1.3 3080.14 684142 217.5 1.4 3188.08 794949 206.7"
## [432] "225.48 4480 269.8 1 1476.1 101749 236.9 439.83 44700 216.2 1.4 2813.21 456591 195.5 0.8 3080.52 684419 219.4 1.0 3190.28 798893 193.6"
## [433] "228.20 4573 271.5 0.8 1505 103465 228.1 441.02 45010 214.6 0.2 2814.32 458049 190.7 1.9 3081.25 684949 219.5 1.1"
## [434] "232.05 4703 270.7 0.5 1526.3 104704 236.9 441.8 45222 215.7 0.6 2815.43 459430 194.4 0.7 3081.63 685217 219.7 1.2"
## [435] "233.72 4766 269.3 1 1542.1 105636 230.6 442.76 45466 210.6 0.8 2816.52 460792 199.9 2.6 3082.34 685716 223.5 1.0"
## [436] "236.47 4874 268.6 1.1 1575.2 107579 238.2 444.23 45839 206.6 0.6 2817.25 461687 205.2 0.9 3082.72 685980 224.4 1.3"
## [437] "240.27 5004 269.8 1.2 1582.8 108153 245.6 446.42 46511 203.1 0.9 2817.62 462133 210.0 0.7 3083.37 686425 224.3 1.1"
## [438] "242.50 5094 267.6 0.6 1598 109804 251.2 447.42 46935 200 0.5 2818.72 463456 208.1 2.2 3083.82 686726 227.3 1.7"
## [439] "244.72 5160 265.3 1.7 1615 111862 256.7 447.93 47175 199.1 0.7 2819.83 464866 204.4 1.9 3084.56 687227 228.7 1.3"
## [440] "248.02 5274 265.2 0.8 1627.9 113262 266.3 449.24 47916 202.1 0.6 2820.92 466265 203.4 1.2 3084.92 687470 228.8 1.5"
## [441] "250.72 5370 267.6 2 1637.6 114096 261.4 450.05 48488 206.9 0.6 2822.01 467602 205.5 0.9 3085.65 687949 232.3 1.0"
## [442] "253.50 5476 265.9 0.9 1644 114601 274.5 450.83 49104 206.9 0.7 2822.66 468323 206.5 0.9 3086.03 688195 233.0 0.5"
## [443] "256.27 5562 265.5 0.8 1651 115118 273.2 452.33 50357 212.3 0.5 2823.11 468810 215.5 2.3 3086.73 688652 235.8 1.1"
## [444] "259.02 5657 260.7 1.6 1669.2 116501 262.5 452.99 50928 214.3 1.1 2823.76 469470 218.7 0.9 3087.08 688881 234.9 1.2"
## [445] "260.65 5716 266.7 0.9 1687.2 117750 267.6 453.52 51367 218 0.7 2824.22 469941 229.2 1.4 3087.76 689304 235.8 2.0"
## [446] "264.50 5855 265.5 0.8 1700.9 118649 273.7 455.16 52618 216.9 0.7 2824.86 470597 232.7 0.7 3088.23 689603 239.9 0.6"
## [447] "268.37 5998 263.2 0.6 1716 119672 271.9 456.72 53630 211.7 0.7 2825.31 471046 243.7 1.8 3088.93 690057 235.6 1.3"
## [448] "269.42 6039 262.7 0.9 1726.8 120382 265.2 457.62 54250 210.8 0.7 2826.05 471763 243.9 1.1 3089.30 690294 234.8 2.1"
## [449] "272.20 6131 261.2 0.7 1736.8 121017 277.6 458.73 55053 208 0.9 2826.42 472095 245.6 0.9 3090.05 690771 240.0 2.1"
## [450] "276.07 6263 261.1 0.4 1758.2 122344 272.1 459.81 55927 211.5 0.6 2827.53 473102 241.2 1.7 3090.42 690999 234.0 0.8"
## [451] "278.27 6354 259.4 0.6 1770 123070 276.4 461.92 57477 218.2 0.7 2828.63 474162 233.1 0.6 3091.13 691432 235.6 1.0"
## [452] "280.53 6434 262.1 0.9 1789.2 124213 268.7 464.13 58891 220.4 0.9 2829.72 475218 232.8 1.1 3091.52 691672 236.6 0.7"
## [453] "283.72 6545 262.9 0.5 1790 124257 266.6 465.02 59474 215 0.9 2830.82 476240 236.6 1.0 3092.16 692057 235.5 0.9"
## [454] "285.97 6617 258.1 1.4 1799 124789 266.3 465.74 59955 214.9 0.6 2831.93 477162 239.1 0.9 3092.62 692338 235.9 1.4"
## [455] "288.17 6713 257.6 0.9 1804 125081 279.7 466.48 60431 212.5 0.7 2832.56 477719 236.5 1.2 3093.33 692765 232.9 0.6"
## [456] "292.00 6838 262.3 0.9 1807 125262 273.0 467.78 61239 204.6 0.4 2833.02 478124 231.3 1.0 3093.70 692990 234.8 1.5"
## [457] "294.75 6941 263.0 0.7 1810 125434 277.1 470.18 62751 197.4 0.5 2833.66 478721 220.8 0.7 3094.45 693433 234.1 1.5"
## [458] "297.52 7028 260.7 0.6 1825.7 126347 273.7 470.92 63205 203.6 1 2834.12 479144 218.8 2.3 3094.80 693639 234.1 1.3"
## [459] "299.72 7112 258.4 0.8 1830 126598 267.1 2835.22 480108 223.8 1.4 3095.53 694068 235.4 1.0"
## [460] "303.00 7234 260.1 0.6 1836 126886 262.5 2836.32 481035 223.4 1.7 3095.92 694300 234.4 1.1"
## [461] "305.75 7320 260.4 0.4 1841.6 127132 262.6 2837.43 481932 227.3 1.3 3096.56 694672 235.8 1.3"
## [462] "308.52 7413 259.7 0.9 1852.4 127622 275.3 2838.53 482803 231.4 1.1 3097.02 694941 236.9 0.8"
## [463] "311.26 7507 259.2 0.7 1859 127907 275.6 2839.62 483649 231.4 1.3 3097.74 695383 236.7 1.9"
## [464] "314.00 7590 260.8 1.4 1869.3 128344 274.0 2840.71 484465 231.2 1.2 3098.13 695618 237.6 0.7"
## [465] "316.75 7691 259.6 0.5 1870 128372 287.1 2841.81 485276 233.0 1.4 3098.85 696062 234.6 1.0"
## [466] "319.52 7781 259.3 0.9 1875.9 128609 286.8 2842.92 486043 232.9 1.2 3099.22 696287 234.8 0.6"
## [467] "322.27 7876 258.3 1.2 1882.5 128866 282.6 2844.02 486816 231.3 1.2 3099.93 696717 235.4 0.8"
## [468] "325.00 7990 261.3 0.9 1890 129146 264.1 2845.11 487541 237.1 1.8 3100.32 696963 232.9 0.6"
## [469] "326.55 8050 260.7 0.4 1895 129340 263.4 2846.22 488268 242.0 0.2 3100.92 697331 232.4 0.7"
## [470] "330.50 8181 261.8 1 1902 129652 257.9 2846.86 488689 240.9 0.4 3101.43 697660 232.2 0.5"
## [471] "333.27 8281 259.0 1.1 1903.5 129736 259.0 2847.33 488996 252.8 2.5 3102.13 698120 231.0 1.0"
## [472] "336.02 8387 260.9 0.7 1930 131329 245.0 2848.05 489475 249.3 2.7 3102.52 698386 228.0 0.5"
## [473] "338.65 8477 260.4 0.6 1932 131455 240.4 2848.42 489722 242.6 0.6 3103.25 698880 226.4 1.0"
## [474] "341.50 8579 259.3 1 1936 131728 228.9 2849.53 490445 243.3 1.3 3103.57 699102 227.7 0.7"
## [475] "343.72 8653 262.0 0.8 1947 132492 223.5 2850.63 491191 246.7 1.6 3104.33 699633 227.6 1.6"
## [476] "347.02 8784 263.7 1.2 1954.5 133069 223.9 2851.72 491959 243.7 1.4 3104.71 699909 226.0 0.3"
## [477] "349.75 8869 263.8 0.8 1955 133105 220.3 2852.82 492738 239.7 1.9 3105.36 700389 228.7 1.3"
## [478] "352.58 8973 265.2 0.9 1960 133427 210.6 2853.91 493507 239.1 1.2 3105.82 700744 227.6 1.1"
## [479] "355.82 9092 260.6 1.7 1969.8 134123 208.9 2855.03 494311 238.3 2.0 3106.46 701242 228.2 0.5"
## [480] "357.47 9140 260.9 0.6 1972 134287 203.7 2856.12 495085 238.5 1.4 3106.92 701606 228.8 1.4"
## [481] "360.20 9232 263.0 0.4 1980.2 134960 204.5 2857.22 495853 237.6 1.6 3107.64 702158 229.3 0.5"
## [482] "362.98 9317 263.8 1.2 1982 135114 200.4 2858.32 496608 236.4 2.1 3107.93 702381 230.3 1.7"
## [483] "369.55 9536 264.4 0.4 1983 135207 198.0 2859.43 497366 236.5 1.7 3108.65 702988 232.4 1.3"
## [484] "371.23 9597 264.2 0.9 1987.4 135603 198.0 2860.51 498104 232.8 0.8 3109.12 703384 232.8 1.6"
## [485] "375.05 9721 264.0 0.3 1990.6 135883 201.7 2861.62 498865 230.6 0.5 3109.75 703934 231.2 1.8"
## [486] "377.27 9807 263.4 0.1 1992 136011 200.7 2862.72 499610 230.8 1.0 3110.07 704211 231.2 0.9"
## [487] "380.00 9909 265.7 0.5 1994.6 136251 202.4 2863.83 500363 228.2 1.7 3110.88 704973 233.9 0.8"
## [488] "382.22 9983 264.9 0.4 1998 136567 195.8 2864.93 501130 230.8 1.4 3111.32 705410 228.5 1.5"
## [489] "385.13 10088 267.5 0.4 1999 136655 201.1 2866.02 501866 231.2 0.8 3112.05 706141 228.6 1.0"
## [490] "388.23 10209 266.9 0.6 2005.8 137293 194.3 2867.13 502625 232.0 1.6 3112.31 706409 228.1 1.0"
## [491] "390.45 10294 266.0 1.1 2009.5 137633 193.4 2868.23 503375 232.2 1.4 3115.25 709680 219.7 0.6"
## [492] "393.78 10417 265.1 1.6 2013 137982 194.2 2869.32 504083 234.1 0.8 3115.72 710237 220.2 0.3"
## [493] "396.50 10527 267.6 0.7 2015 138185 190.2 2870.42 504777 233.9 1.1 3116.42 711104 218.9 1.5"
## [494] "399.28 10621 264.8 0.6 2025.7 139275 192.3 2871.52 505516 235.5 1.8 3116.68 711421 218.7 1.4"
## [495] "402.00 10744 264.8 0.4 2029 139617 196.5 2872.62 506287 236.0 2.1 3117.81 712833 218.5 0.5"
## [496] "404.19 10805 265.0 0.8 2041 140899 195.6 2873.72 507011 238.2 0.9 3118.60 713843 222.3 1.6"
## [497] "404.78 10827 265.3 0.4 2041.5 140960 196.4 2874.82 507714 237.0 0.8 3118.95 714288 221.7 2.0"
## [498] "406.39 10895 264.4 1.5 2050.3 142058 190.4 2875.92 508476 240.3 0.7 3119.67 715180 217.7 0.6"
## [499] "407.50 10933 264.1 0.7 2077.5 145363 196.9 2877.02 509247 233.4 1.0 3120.12 715750 222.1 0.6"
## [500] "409.70 11014 264.2 1.1 2107.05 148831 203.0 2878.12 510008 236.4 1.4 3120.85 716704 208.1 0.7"
## [501] "411.38 11087 264.5 0.4 2116 149803 191.9 2879.22 510765 235.2 0.5 3121.13 717065 205.0 1.7"
## [502] "413.03 11136 264.0 0.5 2117 149921 188.9 2880.32 511515 242.0 0.8 3121.86 718064 192.9 1.2"
## [503] "414.75 11201 263.0 1.3 2131.1 151423 200.6 2881.42 512269 238.2 1.0 3122.32 718779 184.3 1.1"
## [504] "415.73 11236 265.2 0.8 2157 154480 189.0 2882.52 512997 239.2 1.2 3122.95 719794 187.8 1.6"
## [505] "417.07 11278 258.8 0.7 2164 155395 185.5 2883.62 513724 241.5 1.3 3123.35 720337 195.2 0.8"
## [506] "418.53 11338 260.8 0.5 2167.2 155813 187.5 2884.72 514429 243.0 0.5 3124.06 721318 206.3 0.8"
## [507] "420.49 11392 255.4 0.3 2203 159562 204.3 2885.82 515113 247.2 2.2 3124.52 722039 211.3 0.9"
## [508] "421.80 11436 253.9 0.6 2207.3 159943 196.5 2886.92 515771 246.2 2.6 3125.27 723133 213.4 1.2"
## [509] "422.90 11469 253.8 0.8 2225 161679 191.6 2888.02 516417 245.5 1.1 3125.53 723464 213.2 1.3"
## [510] "426.10 11580 250.7 1.1 2231.05 162228 190.1 2889.12 517069 245.3 1.3 3126.27 724445 210.3 2.0"
## [511] "427.33 11635 249.7 0.4 2240.15 163024 186.7 2890.22 517706 247.7 1.4 3126.72 725059 206.3 0.7"
## [512] "428.30 11676 251.1 0.3 2247 163698 183.8 2891.32 518334 245.5 0.8 3127.41 725937 206.6 1.8"
## [513] "429.50 11727 250.7 0.9 2254.05 164439 196.6 2892.42 518965 243.5 0.7 3127.73 726322 208.1 1.2"
## [514] "431.73 11819 245.3 1.1 2280 167183 197.8 2895.71 520892 241.9 1.4 3128.45 727192 204.5 0.4"
## [515] "433.79 11896 245.3 0.6 2302 169492 197.7 2896.82 521552 236.8 0.8 3128.91 727732 205.5 1.3"
## [516] "435.00 11958 246.6 0.5 2316.05 171351 196.0 2897.92 522216 235.8 1.2 3129.62 728568 205.1 1.1"
## [517] "437.23 12050 243.2 0.4 2325 172434 190.3 2899.02 522923 233.7 0.7 3129.93 728921 205.4 0.8"
## [518] "438.85 12122 240.3 0.3 2331.05 173135 189.4 2900.12 523666 230.3 0.8 3131.12 730299 204.0 1.6"
## [519] "443.80 12371 237.5 0.5 2333 173394 190.1 2901.22 524409 227.8 0.6 3131.75 730949 204.1 0.8"
## [520] "446.03 12496 237.6 0.6 2348 175306 207.7 2902.32 525164 224.7 1.9 3132.13 731329 204.9 0.8"
## [521] "448.75 12642 234.2 0.3 2363 177139 213.2 2903.42 525908 222.7 1.0 3132.92 732141 203.8 1.0"
## [522] "450.98 12760 238.3 1.1 2372 178179 217.7 2904.51 526661 221.2 1.2 3133.32 732548 205.9 1.7"
## [523] "454.25 12942 237.3 0.5 2379.2 179117 198.1 2905.62 527454 220.3 0.5 3134.02 733261 203.9 0.7"
## [524] "457.03 13090 237.9 0.2 2386 180068 199.7 2906.72 528262 220.7 0.9 3134.33 733543 204.4 0.3"
## [525] "459.90 13241 237.6 0.6 2399 182046 203.4 2907.36 528747 214.5 0.5 3135.06 734223 205.3 0.4"
## [526] "463.63 13440 236.4 0.9 2414 184685 210.7 2907.82 529101 211.4 2.2 3135.52 734604 207.4 1.9"
## [527] "465.25 13542 239.2 0.5 2425 186697 231.3 2908.48 529640 204.4 0.6 3136.19 735167 201.7 1.2"
## [528] "467.45 13653 238.6 0.6 2437 188436 231.4 2908.92 530016 200.0 0.8 3136.53 735459 201.3 0.8"
## [529] "470.20 13804 238.6 0.3 2442.05 189076 220.3 2909.65 530685 195.1 0.7 3137.25 736079 204.1 1.0"
## [530] "473.06 13948 239.1 0.4 2451 190352 218.0 2910.02 531035 193.8 0.8 3137.72 736460 209.7 1.8"
## [531] "479.71 14303 228.5 0.6 2470.3 192910 226.5 2910.66 531662 190.5 1.7 3138.44 737034 208.1 0.7"
## [532] "484.10 14550 228.4 0.7 2475 193481 220.0 2911.12 532119 199.8 1.2 3138.73 737266 211.3 0.8"
## [533] "487.25 14725 226.1 0.6 2488.05 195017 226.4 2912.22 533246 199.4 0.8 3139.46 737889 210.6 1.4"
## [534] "490.03 14890 225.2 0.5 2494.1 195673 241.2 2913.33 534364 205.0 0.9 3139.89 738272 206.5 1.7"
## [535] "492.20 15012 224.5 0.6 2499 196179 242.6 2914.42 535483 206.4 0.7 3140.54 738844 200.3 1.6"
## [536] "496.07 15233 222.0 0.8 2525 198972 250.9 2915.52 536622 212.9 1.3 3140.88 739137 197.8 1.5"
## [537] "499.35 15438 221.0 0.8 2533 199918 239.1 2916.62 537770 211.2 0.7 3141.66 739842 185.0 0.9"
## [538] "501.58 15570 220.9 0.5 2543 201163 247.6 2917.72 538959 205.0 0.8 3142.12 740277 178.9 0.3"
## [539] "504.20 15742 219.4 0.6 2552.01 202413 244.4 2918.82 540154 203.6 1.2 3142.85 741021 178.6 2.4"
## [540] "506.53 15886 214.0 0.8 2554.91 202874 231.9 2919.92 541345 208.1 0.8 3143.13 741307 176.6 2.4"
## [541] "509.25 16073 207.5 0.9 2557.71 203317 232.2 2921.00 542502 210.3 1.6 3143.86 742075 177.9 2.1"
## [542] "512.03 16260 207.7 0.5 2560.91 203837 228.6 2922.12 543676 209.6 1.6 3144.32 742558 182.3 1.3"
## [543] "514.75 16452 202.9 0.7 2564.91 204480 226.3 2923.22 544804 209.7 0.8 3144.98 743233 181.7 2.7"
## [544] "517.53 16659 200.8 1 2567.51 204908 229.4 2924.32 545956 204.6 1.9 3145.32 743589 180.4 0.7"
## [545] "520.25 16870 195.2 0.3 2570.41 205362 231.4 2925.42 547013 202.5 1.6 3146.06 744354 181.2 0.9"
## [546] "523.03 17111 193.9 0.5 2574.21 205952 238.1 2926.07 547573 208.8 0.7 3146.52 744843 182.0 0.9"
## [547] "526.30 17375 191.0 0.5 2575.51 206144 237.2 2926.52 547972 213.6 0.9 3147.48 745836 180.2 1.2"
## [548] "528.53 17565 188.5 0.7 2579.91 206810 230.0 2927.62 548933 215.2 0.5 3148.26 746643 183.1 0.4"
## [549] "531.25 17809 188.5 0.7 2581.91 207120 240.5 2928.72 549830 219.9 0.5 3148.72 747110 180.8 0.3"
## [550] "532.93 17943 189.2 0.4 2584.71 207544 242.2 2929.82 550637 221.7 1.4 3149.35 747759 180.8 1.3"
## [551] "536.75 18285 187.0 0.2 2588.81 208064 244.6 2930.48 551124 222.3 0.9 3149.68 748101 180.4 0.8"
## [552] "539.53 18541 188.6 0.5 2590.41 208254 243.9 2930.92 551452 226.3 0.9 3150.45 748913 181.4 1.3"
## [553] "542.90 18828 189.4 0.4 2595.11 208803 247.2 2931.65 551979 222.1 1.1 3150.91 749401 182.9 1.8"
## [554] "543.35 18868 192.3 0.6 2596.71 208995 252.0 2932.02 552250 220.3 0.3 3151.65 750194 184.8 1.6"
## [555] "543.93 18921 188.3 0.6 2600.41 209432 246.9 2933.12 552961 223.6 1.1 3151.91 750476 184.0 1.4"
## [556] "548.85 19347 188.7 0.2 2603.71 209817 239.5 2934.22 553626 224.3 2.2 3152.65 751301 186.2 1.9"
## [557] "550.51 19509 188.8 0.5 2606.61 210154 257.4 2935.32 554254 226.7 1.2 3153.12 751830 190.1 1.3"
## [558] "553.25 19748 190.0 0.8 2612.51 210813 243.4 2936.42 554831 233.9 1.5 3153.78 752605 188.0 0.3"
## [559] "556.03 19988 188.0 0.9 2621.71 211858 251.2 2937.52 555345 241.0 1.4 3154.10 752978 196.5 1.8"
## [560] "557.89 20168 188.2 0.7 2629.41 212716 241.4 2938.17 555637 243.0 0.8 3154.96 753984 191.5 1.7"
## [561] "558.20 20197 195.0 0.7 2634.41 213270 240.3 2938.61 555839 249.1 2.1 3155.32 754394 195.8 1.5"
## [562] "561.53 20502 187.8 0.4 2636.71 213536 242.6 2939.27 556143 244.0 1.5 3156.08 755241 200.5 2.0"
## [563] "564.26 20748 186.9 0.3 2640.41 213984 247.5 2939.71 556364 250.5 0.8 3156.30 755495 201.9 1.4"
## [564] "567.03 21011 186.5 0.3 2644.41 214459 251.7 2940.47 556724 245.6 1.3 3157.05 756357 206.0 2.2"
## [565] "569.75 21257 184.7 1.2 2646.61 214794 251.1 2940.82 556889 240.4 0.9 3157.52 756871 210.7 2.3"
## [566] "572.53 21507 186.1 0.4 2650.41 215382 245.3 2941.91 557385 238.1 1.2 3158.15 757561 215.0 1.5"
## [567] "576.33 21854 185.7 1.3 2656.21 216352 240.5 2943.01 557887 234.5 1.0 3158.53 757962 219.2 1.4"
## [568] "578.11 22015 184.4 0.8 2666.71 218361 214.1 2943.66 558183 229.7 0.4 3158.80 758259 215.3 0.7"
## [569] " 2670.41 219116 216.1 2944.12 558393 230.2 0.7 3159.00 758475 217.6 1.8"
## [570] " 2674.61 220058 207.1 2945.22 558929 230.3 1.5 3159.35 758883 217.9 2.3"
## [571] " 2677.41 220739 208.8 2946.32 559461 228.3 0.9 3159.72 759306 214.9 1.2"
## [572] " 2682.61 222030 205.6 2947.42 559972 231.6 1.2 3160.47 760202 208.8 0.8"
## [573] " 2691.01 224269 203.3 2948.52 560459 231.9 1.2 3160.71 760500 206.9 1.1"
## [574] " 2693.61 224923 215.7 2949.62 560930 234.6 1.5 3161.46 761453 206.1 1.9"
## [575] " 2698.01 225909 235.5 2950.53 561309 234.1 0.9 3161.92 762064 212.0 0.2"
## [576] " 2701.41 226711 234.5 2951.82 561846 240.1 2.1 3162.55 762871 216.0 2.1"
## [577] " 2702.71 227027 233.1 2952.92 562272 242.3 0.5 3162.91 763319 215.0 0.9"
## [578] " 2705.61 227776 224.5 2954.02 562690 245.7 1.8 3163.20 763686 225.7 3.0"
## [579] " 2711.71 229423 232.4 2955.12 563115 245.8 0.5 3163.40 763934 221.4 2.7"
## [580] " 2715.41 230422 233.9 2956.22 563517 247.6 1.5 3163.65 764249 224.1 1.4"
## [581] " 2717.71 231066 241.6 2957.32 563918 251.4 1.7 3164.12 764833 222.6 0.9"
## [582] " 2732.71 234817 245.2 2958.42 564311 252.4 1.7 3164.84 765735 216.8 1.6"
## [583] " 2735.71 235480 252.1 2959.52 564699 252.6 1.0 3165.13 766110 215.7 0.5"
## [584] " 2738.71 236114 241.4 2960.62 565077 251.4 0.7 3165.86 767096 213.5 0.4"
## [585] " 2741.71 236734 247.4 2961.72 565466 253.7 0.8 3166.32 767737 217.7 0.9"
## [586] " 2744.61 237294 243.1 2962.82 565851 254.3 1.6 3166.97 768655 222.4 2.1"
## [587] " 2747.61 237868 239.1 2963.92 566233 253.9 0.7 3167.26 769050 221.4 1.8"
## [588] " 2751.11 238558 245.6 2965.01 566619 254.5 1.6 3167.60 769514 228.1 1.6"
## [589] " 2753.61 239013 245.8 2966.12 567007 253.2 0.9 3167.80 769787 226.0 1.6"
## [590] " 2756.21 239477 247.4 2967.19 567381 253.9 1.2 3168.05 770133 231.5 1.9"
## [591] " 2759.11 239973 252.8 2968.32 567777 252.8 1.1 3168.29 770447 235.6 1.1"
## [592] " 2765.21 240945 259.7 2969.42 568167 253.0 0.6 3168.50 770724 238.2 2.2"
## [593] " 2768.2 241366 263.2 2970.52 568556 250.2 0.4 3168.70 770994 235.6 2.1"
## [594] " 2773.51 242007 279.0 2971.62 568946 251.3 1.3 3168.90 771260 237.7 2.4"
## [595] " 2776.51 242346 280.2 2972.71 569331 250.0 1.3 3169.24 771708 229.5 1.5"
## [596] " 2782.71 243071 263.7 2973.82 569728 251.3 1.3 3169.53 772076 230.9 1.0"
## [597] " 2785.51 243429 252.3 2974.92 570139 251.8 1.2 3170.25 773043 230.0 2.3"
## [598] " 2788.51 243856 249.9 2976.02 570548 251.8 1.3 3170.72 773680 233.3 0.9"
## [599] " 2791.5 244347 236.7 2977.12 570955 249.6 0.5 3171.35 774548 236.9 0.4"
## [600] " 2794.51 244864 230.4 2978.22 571367 251.6 1.7 3171.73 775051 240.5 0.6"
## [601] " 2797.51 245441 219.4 2979.32 571775 250.3 1.0 3172.46 776037 238.8 2.0"
## [602] " 2806.51 247681 214.7 2980.41 572190 246.3 1.1 3172.92 776636 243.9 0.7"
## [603] " 2815.61 250133 200.2 2981.52 572619 247.7 0.7 3173.65 777556 246.3 0.5"
## [604] " 2818.61 251005 213.9 2982.62 573037 249.2 1.1 3173.93 777900 246.1 1.1"
## [605] " 2821.51 251864 195.4 2983.72 573462 248.7 0.4 3174.65 778798 245.8 2.4"
## [606] " 2824.51 252739 196.7 2984.82 573902 251.8 1.8 3175.11 779364 243.9 0.9"
## [607] " 2827.51 253636 195.4 2985.92 574353 251.9 0.7 3175.84 780268 248.5 0.6"
## [608] " 2833.81 255498 199.0 2987.02 574803 252.1 1.3 3176.13 780612 242.8 0.7"
## [609] " 2836.51 256309 201.9 2988.12 575265 248.9 1.0 3176.89 781535 248.7 0.7"
## [610] " 2839.51 257100 204.0 2989.22 575730 252.5 0.5 3177.32 782059 246.2 1.1"
## [611] " 2845.51 258661 203.9 2990.32 576222 252.9 1.1 3178.31 783263 252.1 2.5"
## [612] " 2851.51 260353 209.6 2991.42 576723 251.3 1.1 3179.05 784147 246.9 0.7"
## [613] " 2853.51 260916 205.7 2992.52 577242 251.3 1.1 3179.52 784692 250.7 0.2"
## [614] " 2857.51 262092 208.9 2993.62 577769 251.1 0.6 3180.15 785413 253.3 2.6"
## [615] " 2860.51 262930 214.6 2994.72 578305 249.1 0.5 3180.51 785789 255.4 1.4"
## [616] " 2866.51 264509 228.1 2995.82 578857 252.9 1.1 3181.26 786587 260.3 1.3"
## [617] " 2870.51 265653 199.9 2996.92 579435 251.5 1.8 3181.73 787076 256.9 0.7"
## [618] " 2872.71 266326 211.7 2997.65 579821 244.1 1.7 3182.43 787805 248.1 1.5"
## [619] " 2876.21 267442 188.7 2998.02 580019 243.8 0.9 3182.65 788033 247.9 2.7"
## [620] " 2878.5 268181 187.2 2998.66 580400 236.2 0.3 3183.46 788887 229.5 0.8"
## [621] " 2881.42 269154 194.2 2999.12 580695 230.3 0.6 3183.91 789381 226.3 3.0"
## [622] " 2884.51 270222 198.8 2999.76 581160 225.2 1.6 3184.57 790153 218.2 0.8"
## [623] " 2887.51 271256 184.7 3000.22 581507 219.4 0.8 3184.90 790538 221.3 1.8"
## [624] " 2890.51 272311 190.4 3000.86 582000 215.4 1.1 3185.66 791491 215.4 3.7"
## [625] " 2893.51 273310 193.9 3001.32 582391 209.9 1.2 3186.12 792081 205.1 2.5"
## [626] " 2896.51 274321 194.1 3002.05 583034 206.7 0.5 3186.75 792943 204.0 1.6"
## [627] " 2899.51 275350 198.4 3002.42 583413 210.6 0.6 3186.98 793260 209.0 1.9"
## [628] " 2902.51 276326 193.2 3005.26 586406 224.0 0.9 3187.87 794608 199.4 1.7"
## [629] " 2905.51 277361 202.2 3005.72 586893 226.0 1.4 3188.23 795202 195.2 2.0"
## [630] " 2908.51 278350 204.5 3006.45 587647 234.4 0.5 3188.98 796467 189.3 2.1"
## [631] " 2911.46 279320 211.0 3006.82 588034 238.8 1.0 3189.33 797099 188.4 1.4"
## [632] " 2914.51 280269 215.3 3007.46 588716 246.3 1.8 3190.08 798512 191.0 2.2"
## [633] " 2919.41 281758 223.7 3007.92 589224 250.2 0.4"
## [634] " 2926.51 283785 231.3 3008.56 589868 248.1 0.6"
## [635] " 2932.51 285380 228.0 3009.02 590335 243.6 0.8"
## [636] " 2935.51 286128 226.4 3009.57 590893 237.4 0.8"
## [637] " 2939.31 287036 231.4 3010.85 592279 225.7 1.1"
## [638] " 2941.51 287538 230.4 3011.22 592697 229.4 1.3"
## [639] " 2944.51 288233 231.0 3011.87 593415 233.2 0.3"
## [640] " 2953.5 290153 234.9 3012.28 593870 238.1 0.9"
## [641] " 2956.51 290730 220.4 3012.96 594639 238.0 1.1"
## [642] " 2959.51 291367 217.1 3013.42 595189 232.9 0.6"
## [643] " 2964.51 292405 207.6 3014.06 595950 221.2 1.8"
## [644] " 2967.51 293057 206.0 3014.52 596515 216.4 0.9"
## [645] " 2970.51 293779 206.7 3015.25 597443 216.3 1.5"
## [646] " 2973.81 294568 212.7 3015.62 597966 219.0 1.0"
## [647] " 2979.51 295930 213.1 3016.26 598833 226.0 1.1"
## [648] " 2986.01 297921 217.1 3016.72 599434 229.4 1.4"
## [649] " 2988.61 298741 224.4 3017.82 600882 232.5 1.3"
## [650] " 2991.51 299621 231.0 3018.92 602278 237.9 0.8"
## [651] " 2994.51 300472 236.1 3020.02 603673 239.1 1.1"
## [652] " 2997.51 301402 239.0 3021.12 605076 244.5 0.7"
## [653] " 3000.4 302280 236.0 3022.19 606374 248.5 1.7"
## [654] " 3003.51 303226 240.2 3023.32 607708 254.6 1.2"
## [655] " 3007.01 304232 240.7 3024.42 608929 259.2 1.8"
## [656] " 3009.51 304901 250.2 3025.52 610136 257.7 0.5"
## [657] " 3012.51 305655 248.6 3026.62 611319 259.6 1.2"
## [658] " 3015.51 306547 244.8 3027.72 612514 258.0 1.4"
## [659] " 3018.51 307495 225.8 3028.82 613709 256.0 0.4"
## [660] " 3022.71 308744 227.8 3029.92 614923 252.5 1.1"
## [661] " 3024.91 309389 226.2 3031.02 616227 252.4 0.9"
## [662] " 3027.51 310168 233.2 3032.09 617544 252.3 1.1"
## [663] " 3030.41 311013 237.8 3033.22 618955 247.9 1.0"
## [664] " 3033.51 311868 239.0 3034.32 620338 245.4 0.3"
## [665] " 3036.51 312676 241.9 3035.42 621760 243.0 0.8"
## [666] " 3039.51 313414 251.6 3036.52 623214 238.6 0.8"
## [667] " 3042.51 314144 256.7 3037.62 624690 237.3 1.0"
## [668] " 3045.51 314867 257.1 3038.26 625570 234.3 0.3"
## [669] " 3048.56 315572 246.8 3038.72 626215 227.8 0.9"
## [670] " 3051.51 316200 272.6 3039.36 627211 214.9 0.5"
## [671] " 3054.51 316897 251.6 3039.82 627999 205.0 0.9"
## [672] " 3057.71 317734 245.2 3040.53 629446 198.7 0.8"
## [673] " 3060.51 318559 233.4 3040.92 630295 199.9 0.5"
## [674] " 3063.51 319480 255.8 3041.65 632001 199.5 1.8"
## [675] " 3066.51 320358 249.2 3042.01 632856 195.6 1.5"
## [676] " 3072.51 322015 257.2 3042.74 634592 192.1 1.6"
## [677] " 3075.41 322767 260.4 3043.12 635489 193.9 1.8"
## [678] " 3078.51 323526 260.3 3043.74 636957 193.0 0.7"
## [679] " 3081.6 324280 260.5 3044.22 638127 194.3 1.9"
## [680] " 3084.51 324971 266.2 3044.93 639848 187.7 1.0"
## [681] " 3087.81 325720 264.0 3045.32 640760 189.1 0.5"
## [682] " 3090.51 326321 266.1 3046.05 642405 190.2 1.0"
## [683] " 3093.51 326972 270.1 3046.42 643204 190.4 1.1"
## [684] " 3096.46 327590 271.9 3047.12 644662 194.1 1.3"
## [685] " 3099.51 328221 275.1 3047.52 645470 194.6 0.9"
## [686] " 3105.51 329475 265.0 3048.16 646723 188.6 2.0"
## [687] " 3109.01 330208 271.7 3048.62 647588 190.5 1.0"
## [688] " 3111.51 330740 272.6 3049.36 648946 192.1 0.7"
## [689] " 3114.81 331438 273.1 3049.72 649598 194.8 0.4"
## [690] " 3117.51 331944 282.4 3050.45 650891 187.8 1.2"
## [691] " 3119.51 332285 289.1 3050.82 651556 192.0 0.7"
## [692] " 3120.61 332462 288.4 3051.55 652802 185.8 0.5"
## [693] " 3123.51 332919 298.6 3051.92 653448 185.3 1.0"
## [694] " 3126.51 333380 278.1 3052.56 654473 191.3 1.8"
## [695] " 3129.91 333890 285.8 3053.02 655202 193.2 1.0"
## [696] " 3132.41 334261 278.6 3053.73 656286 198.4 0.5"
## [697] " 3135.51 334748 270.5 3054.12 656882 198.7 0.7"
## [698] " 3138.51 335287 255.7 3054.85 657923 191.3 0.6"
## [699] " 3141.51 335918 241.9 3055.22 658474 189.2 0.9"
## [700] " 3145.01 336725 239.6 3055.93 659524 182.4 0.3"
## [701] " 3147.51 337391 234.2 3056.32 660084 183.9 0.4"
## [702] " 3153.51 339298 250.1 3056.96 660981 186.6 1.0"
## [703] " 3156.51 340456 200.7 3057.42 661650 189.8 0.8"
## [704] " 3159.51 341802 205.2 3058.13 662669 187.8 1.5"
## [705] " 3162.81 343282 204.8 3058.52 663206 189.0 1.0"
## [706] " 3165.51 344446 211.9 3059.25 664192 189.1 1.2"
## [707] " 3169.01 345980 220.3 3059.61 664690 185.8 0.8"
## [708] " 3174.51 348298 221.1"
## [709] " 3177.81 349688 216.2"
## [710] " 3180.51 350925 209.4"
## [711] " 3183.41 352275 209.2"
## [712] " 3189.51 355302 193.0"
## [713] " 3192.51 356898 186.1"
## [714] " 3195.81 358712 185.8"
## [715] " 3200.01 360957 201.2"
## [716] " 3204.71 363385 206.3"
## [717] " 3210.51 366235 201.9"
## [718] " 3213.71 367856 199.9"
## [719] " 3216.45 369446 214.7"
## [720] " 3219.51 371090 224.6"
## [721] " 3222.51 372646 229.6"
## [722] " 3228.91 376568 227.0"
## [723] " 3231.51 378096 240.0"
## [724] " 3234.51 379696 239.1"
## [725] " 3237.51 381132 246.8"
## [726] " 3240.51 382670 245.8"
## [727] " 3246.41 384534 258.1"
## [728] " 3249.51 385398 264.6"
## [729] " 3252.45 386144 259.2"
## [730] " 3258.51 388062 255.2"
## [731] " 3261.51 389946 250.1"
## [732] " 3264.51 391896 266.3"
## [733] " 3267.51 393591 274.6"
## [734] " 3270.6 395116 277.1"
## [735] " 3273.81 396636 278.0"
## [736] " 3276.51 397911 288.9"
## [737] " 3283.51 401109 279.6"
## [738] " 3287.41 402769 281.2"
## [739] " 3289.45 403609 283.6"
## [740] " 3292.91 404968 276.2"
## [741] " 3299.01 407442 285.5"
## [742] " 3301.4 408475 286.9"
## [743] " 3304.41 409750 277.6"
## [744] " 3310.71 412453 274.6"
## [745] " 3316.46 415167 275.7"
## [746] " 3319.44 416545 279.9"
## [747] " 3322.39 417391 278.0"
## [748] " 3325.39 417923 276.3"
## [749] " 3328.19 418544 276.5"
## [750] " 3331.39 419934 266.6"
## [751] " 3334.39 421443 274.0"
## [752] " 3336.99 423207 273.2"
## [753] " 3340.39 428394 229.7"
## [754] " 3343.39 433925 199.0"
## [755] " 3346.51 437580 201.5"
## [756] " 3346.56 437601 207.8"
## [757] " 3349.51 438986 205.9"
## [758] ""
## [759] ""
## [760] ""
## [761] ""
## [762] ""
## [763] ""
## [764] "3. Composite CO2 record (0-800 kyr BP)"
## [765] ""
## [766] "0-22 kyr Dome C (Monnin et al. 2001) measured at University of Bern"
## [767] "22-393 kyr Vostok (Petit et al. 1999; Pepin et al. 2001; Raynaud et al. 2005) measured at LGGE in Grenoble"
## [768] "393-416 kyr Dome C (Siegenthaler et al. 2005) measured at LGGE in Grenoble"
## [769] "416-664 kyr Dome C (Siegenthaler et al. 2005) measured at University of Bern"
## [770] "664-800 kyr Dome C (Luethi et al. (sub)) measured at University of Bern"
## [771] "Timescale EDC3_gas_a"
## [772] ""
## [773] ""
## [774] "Age(yrBP) CO2(ppmv)"
## [775] "137 280.4"
## [776] "268 274.9"
## [777] "279 277.9"
## [778] "395 279.1"
## [779] "404 281.9"
## [780] "485 277.7"
## [781] "559 281.1"
## [782] "672 282.2"
## [783] "754 280.1"
## [784] "877 278.4"
## [785] "950 276.6"
## [786] "1060 279.1"
## [787] "1153 277.7"
## [788] "1233 278.7"
## [789] "1350 277.4"
## [790] "1453 279.2"
## [791] "1552 280"
## [792] "1638 278.9"
## [793] "1733 278.7"
## [794] "1812 278"
## [795] "1931 276.9"
## [796] "2057 276.7"
## [797] "2128 276.7"
## [798] "2212 277.6"
## [799] "2334 277.9"
## [800] "2433 273.9"df21 <- read_table(here("data","luthi_carbon_dioxide.txt"), skip = 773) #import the data, skip the first 773 lines and save it with the name df21##
## -- Column specification --------------------------------------------------------
## cols(
## `Age(yrBP)` = col_double(),
## `CO2(ppmv)` = col_double()
## )df21historic_co2 <- df21 %>% #save the tibble with the name historic_co2
select(c(1,2))%>% #select the first and the second columns
rename(yrbp = 1) %>% #rename column 1 as yrbp
rename(co2 = 2) #rename column 2 as co2#Question 2b
historic_co2_new <- historic_co2 %>% #save the tibble with the name historic_co2_new
select(c(1,2))%>% #select the first 2 columns
rename(yrbp = 1) %>% #rename column 1 as co2
rename(co2 = 2) %>% #rename column 2 as co2
mutate(yrbp = yrbp + 13) #create a new column named yrbp and add 13
nasa_co2_new <- nasa_co2 %>% #save the tibble with the name nasa_co2_new
mutate(date = format(date, format = "%Y")) %>% #create a column date that shows only the year
group_by(date)%>% #group data by date
summarise(co2 = mean(co2))%>% #summarise the mean of co2
mutate(yrbp = 2021 - as.integer(date)) %>% #create column with the name yrbp
select(c(yrbp,co2))
a <- bind_rows(nasa_co2_new, historic_co2_new) #bind the rows of the two tibble
a
```
#Question 2c## Error: attempt to use zero-length variable namedf2c <- read_csv(here("data_cleaned","combined_co2.csv")) #import the data## Rows: 1160 Columns: 2## -- Column specification --------------------------------------------------------
## Delimiter: ","
## dbl (2): yrbp, co2##
## i Use `spec()` to retrieve the full column specification for this data.
## i Specify the column types or set `show_col_types = FALSE` to quiet this message.df2c m <- ggplot() + geom_line( #create a line plot
data = df2c, #use the data df2c
size = 1, #size of the line
mapping = aes(x = yrbp, y = co2), #define the axes
stat = "identity", #no further transformation
position = "identity") + theme_classic() + #position adjustment
labs (
x = "Years before present", #name the axis X
y = "Carbon dioxide [ppm]") + #name the axis Y
scale_x_continuous(trans = "reverse",limits = c(800000,0), labels = scales::comma) #reverse the plot and use limits starting from 800000 to 0.
m_point <- annotate(
geom = "point", #create a point
colour = "red", #the colour is red
shape = 21,
size = 1.5,
stroke = 1.3) #size and shape of the point
m_curve <- annotate( geom ="curve", #uses a curve
x = 100000,
y = 371.3192, #the position of the text
xend = 0, #where the arrow points
yend = 415.6983 +1 , #where the arrow starts
curvature = - 0.5, #how much curve is the line of arrow
arrow = arrow(type = "closed", length = unit(2.5, "mm")), #type and length of arrow
alpha = 0.8,
colour = "red") #the colour of the arrow
m_text <- annotate("text",
x = 220000,
y = 360.3075,
label = "2021 average: \n 417 ppm", #write a text name
hjust = 0.10, vjust = -0.1,
lineheight = 0.8,
colour = "red") #the colour of the text
m + m_point + m_curve + m_text
#Question 3a
df3a <- read_xlsx(here("data","nsidc_sea_ice_daily_extent.xlsx")) #import the data## New names:
## * `` -> ...1
## * `` -> ...2
## * `` -> ...47df3asea_ice_1 <- df3a %>% #save the tibble with the name sea+ice_
fill(...1) %>% #fill values
select(names(df3a[1:46])) %>% #select columns from 1 to 46
pivot_longer(
cols = names(df3a)[3:46],
names_to = c("year")) %>% #make the data set longer and collapse it into new column value
rename(month = ...1, day = ...2, extent = value)%>% #rename columns
mutate(year = as.integer(year)) %>% #convert year as integer
mutate(day = as.integer(day)) %>% #convert day as integer
mutate(month = match(month, month.name)) #convert month as a number
sea_ice_1#Question 3b
baseline_1979 <- sea_ice_1 %>% #save tibble in baseline_1979
filter(year == 1979) %>% #choose the year 1979
group_by(month) %>% #group by month
summarise(baseline_mean = mean(extent, na.rm=TRUE)) #summarise the mean of baseline and remove missing values
baseline_1979sea_ice_2 <- sea_ice_1 %>% #save tibble in sea_ice_2
group_by(year, month) %>% #group by year and month
summarise(mmean = mean(extent, na.rm=TRUE))%>% #summarise the mean of extent and remove missing value
full_join(baseline_1979) %>% #merge the data setw of baseline_1979
mutate(proportion_baseline_extent = mmean / baseline_mean)%>% #create a column with the averages
select(c(year, month, proportion_baseline_extent)) #select this columns## `summarise()` has grouped output by 'year'. You can override using the `.groups` argument.## Joining, by = "month"sea_ice_2#Question 3c
sea_ice_plot <- sea_ice_2 %>% #save the tibble with the name sea_ice_plot
filter(year != 1978 & year != 2021) %>% #pick rows with of all values except 1978 and 2021
mutate(Month = month.name[month]) #convert month to a number
p <- ggplot(sea_ice_plot, mapping = aes(x = year, y = Month)) #create a plot and define the axis
p +scale_y_discrete(limits = month.name)+ #sort axes y by month
labs(
title = "Sea ice (northern hemisphere)" #add title
) +
geom_tile(aes(fill = proportion_baseline_extent)) + #build the shape
theme(
plot.title = element_text(
hjust = 0.5) #align the title
) +
theme_minimal() + #no background annotations
theme_classic() + scale_fill_distiller(palette = "RdPu", name = "Proportion of 1979 extent") + scale_x_continuous(expand = c(0, 0)) #use the colour and remove the blank space 
#Question 4a
stop_search_1 <- read_csv(file = here("data","stop_and_search.csv")) #import the data ## New names:
## * `` -> ...14## Rows: 16444 Columns: 14## -- Column specification --------------------------------------------------------
## Delimiter: ","
## chr (13): Measure, Time, Time_type, Ethnicity, Ethnicity_type, Legislation_t...
## dbl (1): ...14##
## i Use `spec()` to retrieve the full column specification for this data.
## i Specify the column types or set `show_col_types = FALSE` to quiet this message.stop_search_1stop_search_1 %>%
rename(stops = "Number of stop and searches") %>% #rename the column to stops
rename(year = Time) %>% #rename the column to year
rename(population = "Population by ethnicity") %>% #rename the column to population
rename(rate = "Rate per 1,000 population by ethnicity")%>% #rename the column to rate
select(c(year,Ethnicity,Legislation_type,Geography,stops,population,rate)) %>% #select the columns
filter (Ethnicity %in% c ( "All", "Asian", "Black", "White", "Other" )) %>% #select the rows with the ethicities in the brakets
mutate(stops = as.double(stops)) %>% #convert stops as double
mutate(population = as.double(population)) %>% #convert population as double
mutate(rate = as.double(rate)) #convert rate as double ## Warning in mask$eval_all_mutate(quo): NAs introduced by coercion
## Warning in mask$eval_all_mutate(quo): NAs introduced by coercion
## Warning in mask$eval_all_mutate(quo): NAs introduced by coercionQuestion 4c
First Question
How many stops have been made over the years to each ethnicity across UK? Operationalisation -> We compare the number of stops of all ethnicities using the geography and based on the years we have on the data.
d1 <- read_csv(file = here("data_cleaned","stop_search_2.csv")) ## Rows: 2924 Columns: 9## -- Column specification --------------------------------------------------------
## Delimiter: ","
## chr (4): year, ethnicity, legislation_type, geography
## dbl (5): stops, population, rate, rate_white, relative_disparity##
## i Use `spec()` to retrieve the full column specification for this data.
## i Specify the column types or set `show_col_types = FALSE` to quiet this message.q13 <- d1 %>% #save the tibble to the name q13
select(c(ethnicity, stops, year, geography)) %>% #select the columns
filter(geography =="All - including BTP") %>% #select the rows which include "All - including BTP"
mutate(year = substr(year, 1, 4))%>% #show only 4 numbers of year
group_by(ethnicity) #group by ethnicity
pi <- ggplot(q13, mapping = aes(x = factor(year), y = stops)) #create a plot and define axes
pi + geom_point(mapping = aes(colour = ethnicity)) + #create a plot with points and with colour
labs(title = "Stops and Search in Ethnicities in the UK", #add title and name axes
x = "Years", y = "Stops")+
scale_y_continuous(limits = c(0, 1500000), labels = scales::comma) #put limis and change the type that it shows
Question 4c
Second Question
Are the stops by the British transport police more common in London than elsewhere in the UK? Operationalisation -> We compare the number of stops in London with the number of stops anywhere else in the UK
d1 <- read_csv(file = here("data_cleaned","stop_search_2.csv")) ## Rows: 2924 Columns: 9## -- Column specification --------------------------------------------------------
## Delimiter: ","
## chr (4): year, ethnicity, legislation_type, geography
## dbl (5): stops, population, rate, rate_white, relative_disparity##
## i Use `spec()` to retrieve the full column specification for this data.
## i Specify the column types or set `show_col_types = FALSE` to quiet this message.q23 <- d1 %>% #save the tibble with tha name g23
select(c(stops, year, geography)) %>% #select the columns
filter(geography =="London, City of") %>% #select the rows which include "London, City of"
mutate(year = substr(year, 1, 4))%>% #show only 4 numbers of year
group_by(geography =="London, City of") #group by geography =="London, City of"
pa <- ggplot(q23, mapping = aes(x = factor(year), y = stops)) #create a plot and define axes
pa + geom_line(mapping = aes(colour = geography), size = 5) + #map with color and increase the size
labs(title = "Stops and Search in London", #add title and name the axes
x = "Years", y = "Stops")
Question 4c
Third Question
Over the last decade, have the stops of black people been increased more than the white people? Operationalisation -> We compare the number of stops of black and white people in the last 10 years.
d1 <- read_csv(file = here("data_cleaned","stop_search_2.csv")) ## Rows: 2924 Columns: 9## -- Column specification --------------------------------------------------------
## Delimiter: ","
## chr (4): year, ethnicity, legislation_type, geography
## dbl (5): stops, population, rate, rate_white, relative_disparity##
## i Use `spec()` to retrieve the full column specification for this data.
## i Specify the column types or set `show_col_types = FALSE` to quiet this message.q33 <- d1 %>% #save the tibble with tha name g23
select(c(stops, year, ethnicity)) %>% #select the columns
filter(ethnicity == c("White", "Black"))%>% #select the rows which include White and Black
mutate(year = substr(year, 1, 4))%>% #show only 4 numbers of year
filter(year >= "2009" & year<= "2019") %>% #select only the years from 2009 - 2019
group_by(ethnicity == c("White", "Black")) #group by ethnicity
po <- ggplot(q33, mapping = aes(x = factor(year), y = stops)) #create a plot and define axes
po + geom_point(mapping = aes(colour= ethnicity)) + #map with color
labs(title = "Stops of White and Black people over the past 10 years", #add title and name the axes
x = "Years", y = "Stops") +
scale_y_continuous(limits = c(0, 1500000), labels = scales::comma) #put limis and change the type that it shows
#Question 4d
1st Answer
As the figure shows, the number of stops and search decreased until 2017 and then it started to increase again in all ethnicities.
2st Answer
As the figure shows, the number of stops and searches dramatically decrease from 2007 until 2017 whereas there is a small increase in years 2018 and 2019.
3rd Answer
The stops and search of white people seems to be dropped down in oppose to black people which seems to slighly decreased.